M Etemadi

A Sotoodeh

M Toueni

M Foroozanfar

A Kalantari

It is a great honor and privilege for me to record this deep sense of gratitude and indebtedness to my honorable supervisor Prof. M

Resume:

La verticilliose est une maladie vasculaire des plantes dont les symptômes typiques sont un flétrissement des parties aériennes, des feuilles chlorosées puis séchées, et dans les cas de maladie grave la mort de la plante. Au niveau des racines on observe une coloration brune du tissu conducteur. Cette maladie est causée par un champignon du sol du genre Verticillium. Les espèces majeures V. dahliae et V. albo-atrum sont responsables de pertes importantes de rendement sur de nombreuses cultures. Le champignon entre dans la racine par des blessures ou par des fissures au niveau de sites d'émergence de racines latérales, puis il avance vers le cylindre central et envahit les vaisseaux du xylème. Sa croissance reste pendant longtemps limitée aux vaisseaux qu'il colonise en avançant vers les parties aériennes de la plante. Aux stades tardifs, le champignon sort du cylindre central et colonise les autres tissus.

En Europe, V. albo-atrum constitue l'une des principales causes de maladies chez la luzerne pérenne et est à l'origine de pertes économiques très importantes. La capacité de V. albo-atrum de survivre dans le sol ainsi que sa localisation protégée dans le cylindre centrale des plantes infectées en font un pathogène difficile à combattre, la lutte génétique par sélection de variétés tolérantes apparaissant comme une approche prometteuse. Cependant, la capacité des microorganismes pathogènes de s'adapter rapidement à des nouvelles plantes hôtes est une menace bien connue de la durabilité des variétés résistantes.

Au laboratoire, des travaux ultérieurs ont établi que la plante modèle des légumineuses Medicago truncatula, une espèce sauvage proche de la luzerne cultivée, peut être utilisée pour étudier les mécanismes de résistance et sensibilité vis-à-vis de V. alboatrum. Une lignée résistant et une lignée sensible ont été identifiées et l'étude de la descendance d'un croisement entre ces deux lignées a permis d'identifier un locus majeur (Quantitative trait locus, QTL) contrôlant la résistance à une souche de V. albo-atrum isolée de la Luzerne [START_REF] Ben | Natural diversity in the model legume Medicago truncatula allows identification of distinct genetic mechanisms conferring partial resistance to Verticillium wilt[END_REF] Negahi en 6 e co-auteur). Ce travail a également montré qu'il existait une grande biodiversité au sein de l'espèce M. truncatula par rapport à la réponse à cette souche de V. albo-atrum.

Le travail réalisé dans le cadre de cette thèse traite 2 questions : 1) Est-ce que des souches de Verticillium isolées de plantes-hôtes autres que Medicago sp. sont capables d'infecter M. truncatula ? Autrement dit, la biodiversité au sein du champignon permet-elle d'infecter une nouvelle espèce et la biodiversité au sein de M. truncatula permet-elle de résister à une nouvelle souche de Verticillium ?

Pour répondre à ces questions, une collection de 25 lignées de M. truncatula d'origine géographique diverses a été inoculée avec 6 souches de V. albo-atrum et V. dahliae, isolées à partir de la luzerne, de pomme de terre, tomate, de sol ou d'origine inconnue.

L'évolution des symptômes a été suivie pendant 4 semaines et les symptômes ont été notés sur une échelle de 0 (plante saine) à 4 (plante morte). Le score de symptôme maximal (MSS) ainsi que la surface sous les courbes de symptômes (Area under disease progress curve, AUDPC) ont été déterminés. Les résultats montrent que certains isolats étaient capables d'induire des symptômes de maladies chez certaines lignées. L'isolat de luzerne apparaît comme le plus agressive et celui de tomate comme le moins agressive quand on considère les valeurs moyennes de MSS et AUDPC obtenues avec les 25 lignées. La lignée tunisienne TN8.3 était la plus sensible par la moyenne des valeurs avec les 6 isolats, tandis que les lignées françaises F11013-3 et F83005.9 ainsi que la lignée algérienne DZA 45.6 étaient très résistantes aux 6 isolats du champignon.

Pour les deux paramètres MSS et AUDPC, on observe une interaction statistique significative entre génotypes de plantes et isolats de champignon indiquant un contrôle génétique. Les résultats de cette première partie (publication Negahi et al., 2013a) ont permis de choisir un couple de lignées de M. truncatula et un isolat fongique pour ensuite étudier le contrôle génétique de la résistance 2) La seconde question traitée par cette thèse concerne le contrôle génétique de la résistance chez M. truncatula vis-à-vis d'une souche isolée à partir d'une plante hôte autre que Medicago. Est-ce que c'est similaire au contrôle décrit pour l'isolat de luzerne où on a trouvé un seul QTL et probablement un mécanisme monogénique [START_REF] Ben | Natural diversity in the model legume Medicago truncatula allows identification of distinct genetic mechanisms conferring partial resistance to Verticillium wilt[END_REF], ou est-ce que d'autres régions du génome et donc d'autres gènes et mécanismes sont impliqués ?

Pour cette étude, le même croisement que celui pour l'analyse de la réponse à la souche luzerne a été utilisé. Des lignées recombinantes (Recombinant inbred lines, RILs) de ce croisement en génération F7 ont été inoculées avec la souche de V. albo-atrum LPP0323 (isolat de pomme de terre). Les lignées parentales F83005.5 et A17 étaient respectivement résistante et modérément sensible. 116 RILs (au moins 8 plantes par lignée) ont été inoculées dans un plan expérimental randomisé et en 3 répétitions indépendantes. Les symptômes ont été suivis comme décrit dans le paragraphe précédent.

Une forte variabilité génétique et une ségrégation transgressive de la résistance ont été observées parmi les RILs. L'analyse QTL avec les paramètres MSS et AUDPC a conduit à identifier 4 QTLs contrôlant la résistance. La variance phénotypique expliquée par chaque QTL (R2) était modéré, de 3% à 21%. Le signe négatif des effets de gènes additifs montre que les allèles favorables à la résistance venaient tous de la lignée parentale résistante (Publication Negahi et al., 2013b, acceptée).

En conclusion, ces travaux ont mis en évidence que la biodiversité existante aussi bien chez M. truncatula que chez Verticillium présente un potentiel d'apparition de maladie causée par des souches nouvelles mais aussi un réservoir de gènes permettant à la plante de résister à l'attaque du champignon pathogène. Ainis, des QTLs de résistance à une souche de pomme de terre ont été identifiés. Table 1 Table 2 Chapter 2: Materials and methods Fig. 14 Fig. 15 Chapter 1

General introduction 1.1 Legume plants and their importance in agronomy

Legumes, broadly defined by their unusual flower structure, podded fruit, and the ability of 88% of the species examined to date to form nodules with rhizobia, are second only to the Graminiae in their importance to humans [START_REF] Graham | Legumes: Importance and constraints to greater use[END_REF]. The legumes are a diverse and important family of angiosperms. With more than 650 genera and 18 000 species, legumes are the third largest family of higher plants and are second only to grasses in agricultural importance [START_REF] Young | Legume genomes: more than peas in a pod[END_REF]. Botanically named Fabaceae, this family includes a great number of species, especially herbaceous plants such as pea (Pisum sativum), bean (Phaseolus vulgaris) and soybean (Glycine max), and forage such as alfalfa (Medicago sativa) and clover (Trifolium spp.). They are widespread all over the world, but particularly found in mild-to-cold areas [START_REF] Yang | Alfalfa benefits from Medicago truncatula: the RCT1 gene from M. truncatula confers broad-spectrum resistance to anthracnose in alfalfa[END_REF]. They form symbiotic relationships with members of the Rhizobium family of bacteria, together producing enormous quantities of biological nitrogen. In addition to their ability to form associations with Rhizobia, legumes also form symbiotic relationships with mycorrhizal fungi (as do many other plant families).

Thus, legumes are a major source of organic fertilizer and an essential component of most agricultural rotations. Legumes provide the largest single source of vegetable protein in human diets and livestock feed [START_REF] Young | Legume genomes: more than peas in a pod[END_REF].

Medicago sativa L.

Alfalfa or Lucerne (Medicago sativa L.), known as the "Queen of Forages", is a perennial medic and a native of Iran and Central Asia [START_REF] Bingham | Breeding alfalfa which regenerates from callus tissue in culture[END_REF][START_REF] Harrison | A phosphate transporter from Medicago truncatula involved in the acquisition of phosphate released by arbuscular mycorrhizal fungi[END_REF]. It is currently cultivated in Asia, Europe, Australia, and the Americas [START_REF] Benaben | TE7, an inefficien symbiotic mutant of Medicago truncatula Gaertn cv Jemalong[END_REF].

Alfalfa is rich in proteins, vitamins and minerals, providing highly nutritious hay and pasture for animal and dairy production. Like other legume species, alfalfa contributes to the sustainability of agricultural ecosystems because of its capacity for symbiotic nitrogen fixation. Moreover, the combination of its high biomass production, perennial growth habit, and ability to fix atmospheric nitrogen, has led to increased interest in using alfalfa as a biofuel feedstock for production of ethanol and other industrial materials [START_REF] Yang | Alfalfa benefits from Medicago truncatula: the RCT1 gene from M. truncatula confers broad-spectrum resistance to anthracnose in alfalfa[END_REF].

Other valuable attributes of alfalfa include its relatively low input costs, its ability to improve soil fertility, and its use as the predominant source of nectar for honey production [START_REF] Dita | Biotechnology approaches to overcome biotic and abiotic stress constraints in legumes[END_REF].

The genus Medicago also includes annual medics such as M. truncatula (barrel medic), M. polymorpha (burr medic) and M. scutellata (snail medic). Annual medics are utilized as cover crops, short season forage crops, and weed-suppressing smother crops [START_REF] Castillejo | A proteomic approach to studying plant response to create broomrape (Orobanche crenata) in pea (Pisum sativum)[END_REF].

A number of biotic (fungi, bacteria, nematodes, viruses, parasitic plants, insects) and abiotic (drought, freezing, salinity, water logging) stresses are severely affecting the yield of alfalfa and other legumes. Successful crop improvement by application of biotechnology to legumes facing biotic/abiotic constraints will require both a good biological knowledge of the target species and the mechanisms underlying resistance/tolerance to these stresses. The large genome size and the polyploidy of some legumes have hampered this goal. For example, alfalfa is tetraploid and outcrossing which is an obstacle for genetic studies. In order to solve some of these problems two species, Medicago truncatula and Lotus japonicus, have emerged as model plants to investigate the genetics of nodulation and other important processes such as resistance or tolerance to stresses [START_REF] Dita | Biotechnology approaches to overcome biotic and abiotic stress constraints in legumes[END_REF].

Medicago truncatula as a model legume

The value of M. truncatula (Figure 1) was recognized as early as 1939 [START_REF] Crawford | Breeding annual Medicago species for semiarid conditions in Southern Australia[END_REF]. The so-called barrel medic, M. truncatula is a plant of Mediterranean origin which is well adapted to semiarid conditions and is a winter-growing annual. There are several hundred reported ecotypes of M. truncatula, including commercial varieties such as Jemalong, Cyprus and Ghor. Some of these cultivars are commonly grown in rotation with cereal crops in certain regions of Australia. M. truncatula also grows well in greenhouse and several growth cycles can be completed within a year [START_REF] Barker | Medicago truncatula, a model plant for studying 97 the molecular genetics of the Rhizobium-legume symbiosis[END_REF]. M. truncatula has been developed as the first model legume plant. It is autogamous with a short life cycle (6 months), and diploid (2n=2x=16) with a small genome (500 Mbp), which simplifies studies on the genetic mechanisms of responses to abiotic and biotic agents, notably with regard to the nitrogen-fixing symbiosis with rhizobia [START_REF] Barker | Medicago truncatula, a model plant for studying 97 the molecular genetics of the Rhizobium-legume symbiosis[END_REF]. M. truncatula has not a great importance from an agronomic point of view, in Europe and America, but is widely grown on pastures in Australia. It shows high synteny with other legume plants, especially with M. sativa [START_REF] Choi | A sequence-based genetic map of Medicago truncatula and comparison of marker colinearity with M. sativa[END_REF]. But it has a syntenic relationship with other Legume plants, especially with M. sativa (Figure 2). The two species share conserved genome structure and content, and thus M. truncatula can serve as a surrogate for cloning the counterparts of many economically important genes in alfalfa [START_REF] Yang | Alfalfa benefits from Medicago truncatula: the RCT1 gene from M. truncatula confers broad-spectrum resistance to anthracnose in alfalfa[END_REF].

Figure 1 Flower, leaf, pod and seed of Medicago truncatula as a model legume (http://mips.helmholtz-muenchen.de/plant/medi/).

The foremost plant model Arabidopsis thaliana (L.) Heynh has many advantages for plant genomics, with its small size, short generation time, large numbers of offspring and small nuclear genome. Arabidopsis is a dicotyledonous but non-nitrogen-fixing plant, making it important to develop a legume model with its ability to establish symbiotic interactions with rhizobia and mycorrhizae [START_REF] Adam | Now for the hard ones[END_REF]. Another model plant is rice which is a good model for monocotyledonous plants [START_REF] Adam | Now for the hard ones[END_REF]. Arabidopsis thaliana and rice are unable to establish nitrogen-fixing symbiosis with soil rhizobia, Arabidopsis also fails to form symbiotic root mycorrhizae with soil fungi [START_REF] Albrecht | Legume nodulation and mycorrhizae formation; two extremes in host specificity meet[END_REF][START_REF] Oldroyd | Peace talks and trade deals. Keys to long-term harmony in legume-microbe symbioses[END_REF] M. truncatula is amenable to genetic transformation and is more attractive for genetics than allogamous autotraploid M. sativa. Using Jemalong 2HA, transformation (Thomas et al., 1992;[START_REF] Chabaud | Transformation of barrel medic (Medicago truncatula Gaertn.) by Agrobacterium tumefaciens and regeneration via somatic embryogenesis of transgenic plants with the MtENOD12 nodulin promoter fused to the gus reporter gene[END_REF][START_REF] Wang | Agrobacterium-mediated transformation and expression of foreign genes in Medicago truncatula[END_REF], regeneration from protoplasts, asymmetric somatic hybridisation [START_REF] Tian | Asymmetric somatic hybridisation between the annual legumes Medicago truncatula and Medicago scutellata[END_REF]) and transfer of agriculturally important genes such as resistance against alfalfa mosaic virus was feasible [START_REF] Jayasena | Resistance to Alfalfa mosaic virus in transgenic barrel medic lines containing the virus coat protein gene[END_REF]. .16. Thoquet et al. (2002) noted that the three Jemalong lines A17, J5 and J6 could be considered to have an identical genotype (but different to the highly regenerable Jemalong genotype 2HA) [START_REF] Ray | Medicago truncatula as a model for understanding plant interactions with other organisms, plant development and stress biology: past, present and future[END_REF].

Because of the substantive synteny between M. truncatula and M. sativa and M. truncatula and Pisum sativum L, these mapping studies will provide valuable information for fundamental research and translational research with crop legumes [START_REF] Ray | Medicago truncatula as a model for understanding plant interactions with other organisms, plant development and stress biology: past, present and future[END_REF].

The vast amount of sequence data available in M. truncatula make it an excellent resource for translational genomics. The M. truncatula genome sequence provides a ready source for easily accessible DNA markers across legume species, enabling pan-legume comparisons, facilitating linkage mapping, comparative genomics, and marker-assisted selection [START_REF] Choi | A sequence-based genetic map of Medicago truncatula and comparison of marker colinearity with M. sativa[END_REF]). The M. truncatula genome also reveals the scale and scope of biologically important gene families, including disease resistance genes (Ameline- Torregrosa et al., 2008) and legume-specific and legume over represented families [START_REF] Alunni | Genomic organization and evolutionary insights on GRP and NCR genes, two large nodule-specific gene families in Medicago truncatula[END_REF]. Analysis of upstream regions identifies regulatory sequences, which can be mined and utilized to finetune gene expression as part of genetic engineering. The M. truncatula sequence creates a platform for gene discovery and positional cloning. Finally, the essentially complete M.

truncatula genome sequence accelerates physical mapping in related species and provides a scaffold for next-generation sequencing in close relatives like alfalfa [START_REF] Young | Translating Medicago truncatula genomics to crop legumes[END_REF].

Figure 2 A simplified consensus map for eight legume species. Mt, M. truncatula; Ms, alfalfa; Lj, L. japonicus; Ps, pea; Ca, chickpea; Vr, mungbean; Pv, common bean; Gm, soybean. S and L denote the short and long arms of each chromosome in M. truncatula. Syntenic blocks are drawn to scale based on genetic distance. M. sativa in blue, M. truncatula in red [START_REF] Zhu | Bridging model and crop legumes through comparative genomics[END_REF].

Verticillium wilt

The genus Verticillium encompasses a cosmopolitan group of ascomycete fungi, including several phytopathogenic species that cause vascular wilts of plants [START_REF] Klosterman | Diversity, Pathogenicity, and Management of Verticillium Species[END_REF].

Verticillium wilt diseases are mainly caused by two species, Verticillium albo-atrum (Vaa) and Verticillium dahliae (Vd) which differ in morphology, host range, and growth characteristics [START_REF] Schnathorst | Life cycle and epidemiology of Verticillium[END_REF]. Both species are found to cause disease in temperate and subtropical regions but little in the tropics. Vd appears to be favoured by higher temperatures than Vaa, as can be deduced from its geographical distribution [START_REF] Church | Occurrence of Verticillium dahlia on sunflower (Helianthus annuus) in the UK[END_REF][START_REF] Koike | Verticillium wilts of cauliflower in California[END_REF]. These soil-borne fungi are responsible for monocyclic vascular wilt diseases in over 200 dicotyledonous species, including economically important crops [START_REF] Fradin | Physiology and molecular aspects of Verticillium wilt diseases caused by V.dahliae and V.albo-atrum[END_REF]. V. dahliae causes wilt in a wide range of plants, including vegetables (artichoke, eggplant, pepper, potato and tomato), fruits (grapevine, olive and strawberry), flowers (Chrysanthemum), oilseed crops (sunflower), fibre crops (cotton, flax) and woody perennials. V. albo-atrum is considered to have a rather narrow host range and is mainly reported as a pathogen on alfalfa, hop, soybean, tomato and potato. In addition to these crop plants, many weeds are symptomatic or asymptomatic Verticillium hosts. So far, most monocotyledonous plants are considered to be non-host species. Many individual Verticillium isolates are capable of causing a rather wide range of symptom severities or several hosts.

However, some isolates are more host-specialized and thus have a limited host range. These include V. dahlia isolates from mint and cocoa and V. albo-atrum isolates from alfalfa and hop [START_REF] Fradin | Physiology and molecular aspects of Verticillium wilt diseases caused by V.dahliae and V.albo-atrum[END_REF]. The fungus colonises the vascular tissue of roots and shoots, which causes typical wilt symptoms and leads to the death of susceptible plants [START_REF] Fradin | Physiology and molecular aspects of Verticillium wilt diseases caused by V.dahliae and V.albo-atrum[END_REF]. Because of the localisation of the pathogen in the central cylinder, vascular diseases are particularly difficult to control and plants cannot be cured by fungicides once the symptoms are visible. In addition, survival structures may stay viable in the soil for a long time [START_REF] Church | Occurrence of Verticillium dahlia on sunflower (Helianthus annuus) in the UK[END_REF]. The population biology remains the least understood aspect of this plant pathogen. Whereas strains of Vaa were divided into two groups based on their virulence and aggressiveness to alfalfa, (Medicago sativa), Vd is divided based on vegetative compatibility into six groups. Nevertheless, vegetative compatibility groups (VCGs) do not describe the overall genetic diversity among strains, gene flow, or the potential for recombination. They will, however, aid in the deployment of resistant cultivars, preventing pathogen introductions and exploring the evolution of an agronomically important group of phytopathogens [START_REF] Klosterman | Diversity, Pathogenicity, and Management of Verticillium Species[END_REF]. Vd and Vaa cause billions of dollars in annual crop losses worldwide. Yield losses in potato crops may reach 50%, but are more commonly in the range of 10-15%, whereas in lettuce, losses can easily reach 100% [START_REF] Klosterman | Diversity, Pathogenicity, and Management of Verticillium Species[END_REF]. Verticillium wilt is one of the most important pathogens of alfalfa, particularly in Europe, in North America and in the north of Japan. In the USA and Canada yield losses due to the infection of alfalfa with Verticillium spp. may reach 50% [START_REF] Hu | EDS1 in tomato is required for resistance mediated by TIR-class R genes and the receptor-like R gene Ve[END_REF].

Four other plant-pathogenic species historically associated with the genus Verticillium are V.

tricorpus, V. nigrescens, V. nubilum, and V. theobromae [START_REF] Barbara | Plant pathogenic Verticillium species: How many of them are there?[END_REF]. The recent assignment of V. nigrescens and V. theobromae to the genera Gibellulopsis and Musicillium, respectively [START_REF] Zare | Gibellulopsis, a suitable genus for Verticillium nigrescens, and Musicillium, a new genus for V. theobromae[END_REF], reduced the number of plant pathogenic species in the genus Verticillium to four. In addition, both the entomopathogenic V. lecanii and V.

fungicola, a pathogen of agaric basidiomycetes, were assigned to the genus Lecanillium [START_REF] Zare | A revision of the Verticillium fungicola species complex and its affinity with the genus Lecanicillium[END_REF].

1.2.1Verticillium taxonomy

Nees von Essenbeck erected the genus Verticillium in 1816 based on its unique, branched conidiophores, which form whorls capped with flask-shaped and pointed phialides carrying terminal conidia. Although a few species of the genus Verticillium have been associated with ascomycetous teleomorphs, V. dahliae, V. albo-atrum, and V. tricorpus are solely anamorphic with no evidence of sexual recombination or a meiosporic stage [START_REF] Klosterman | Diversity, Pathogenicity, and Management of Verticillium Species[END_REF] [START_REF] Klosterman | Diversity, Pathogenicity, and Management of Verticillium Species[END_REF].

Based on host specificity, two clear subspecific groups in Vaa are recognized. Alfalfa strains of Vaa, are phylogenetically different from non-alfalfa strains that are generally able to cause little or no disease on alfalfa [START_REF] Barbara | Plant pathogenic Verticillium species: How many of them are there?[END_REF]. [START_REF] Bhat | Host range specificity in Verticillium dahliae[END_REF] reported that Vd strains from various host plants were able to infect alfalfa, but that disease was less severe than with a Vaa strain from alfalfa. This grouping is strongly supported by molecular markers and VCG data. A number of strains morphologically described as Vaa form a separate group based on the internal transcribed spacer (ITS) rDNA regions, and thus were designated as Vaa Group2. All other strains of Vaa are referred to as Group1. The resting structures and molecular markers such as random amplification of polymorphic DNA (RAPDs) and ITS sequences all distinguish these two groups. Despite recognizing that the differences are significant enough to elevate Group2 strains to a separate species, they are currently only recognized as a distinct operational taxonomic unit [START_REF] Klosterman | Diversity, Pathogenicity, and Management of Verticillium Species[END_REF].

Unlike Vd and Vaa, V. tricorpus is a successful soil saprophyte, which may not be impeded in its germination and growth by the absence of a potential host [START_REF] Isaac | Speciation in Verticillium[END_REF]. Chlamydospores, microsclerotia, and melanized hyphae serve as survival structures for V. tricorpus. Because it is considered a weak pathogen on many hosts, research has focused on the potential for V.

tricorpus to reduce the impact of Verticillium wilt induced by Vd or Vaa. Co-inoculations of V. tricorpus with Vd in lettuce and artichoke, and Vd or Vaa in potato have resulted in a lower severity of Verticillium wilt or potato early dying symptoms, compared with plants inoculated with either of the latter two species separately [START_REF] Klosterman | Diversity, Pathogenicity, and Management of Verticillium Species[END_REF].

V. longisporum included some of the isolates with relatively long conidia capable of infecting hosts in the Brassicaceae which were formerly placed in V. dahliae, often being referred to as V. dahlia var. longisporum [START_REF] Barbara | Plant pathogenic Verticillium species: How many of them are there?[END_REF].

Population biology of Verticillium spp.

The population biology of Vd has been primarily addressed on the basis of vegetative compatibility groups (VCGs) [START_REF] Leslie | Fungal vegetative compatibility[END_REF] and several molecular markers including RAPDs, restriction fragment length polymorphisms (RFLPs), amplified fragment length polymorphisms (AFLPs) , and specific primers [START_REF] Perez-Artes | Differentiation of cotton-defoliating and nondefoliating pathotypes of Verticillium dahliae by RAPD and specific PCR analyses[END_REF].

There are six main VCGs in Vd [START_REF] Bhat | Characterization of Verticillium dahliae isolates and wilt epidemics of pepper[END_REF] [START_REF] Klosterman | Diversity, Pathogenicity, and Management of Verticillium Species[END_REF].

Molecular genotyping approaches, based on RFLP and AFLP analyses, have been applied for the study of Verticillium spp. populations. [START_REF] Dobinson | Molecular characterization of vegetative compatibility group 4A and 4B isolates of Verticillium dahliae associated with potato early dying[END_REF] applied RFLP to study the genetic diversity of Vd in solanaceous plants (potato, tomato, and eggplant in particular) in North America and discovered that VCG4A strains from potato belonged to at least two distinct genotypes with potential gene flow with the potato seed. Although RFLP subgroupings have been associated with geographical origin of strains, host, pathotype, and VCG, other studies found no correlation between biological properties (VCG, virulence on specific host), geographic origin, and molecular data [START_REF] Klosterman | Diversity, Pathogenicity, and Management of Verticillium Species[END_REF]. Using a single RAPD primer, [START_REF] Korolev | Comparative study of genetic diversity and pathogenicity among populations of Verticillium dahliae from cotton in Spain and Israel[END_REF] clearly differentiated defoliating (D) and nondefoliating (ND) strains. Strains that showed a particular molecular haplotype were distributed over different geographic locations in both countries. Other studies employed AFLPs to measure the genetic diversity among strains within species of Verticillium and relationships among species [START_REF] Klosterman | Diversity, Pathogenicity, and Management of Verticillium Species[END_REF]. [START_REF] Fahleson | Estimation of genetic variation among Verticillium isolates using AFLP analysis[END_REF] primarily analyzed the relationship of Verticillium spp. and the long-spored crucifer strains. Greater than 85% of the variability occurred at the level of individual populations, and ~14.5% of variability could be attributed to differentiation by geographic origin. [START_REF] Collins | Correlation of molecular markers and biological properties in Verticillium dahliae and the possible origins of some isolates[END_REF] found that groups α and β of the long-spored Verticillium strains from crucifers formed two clusters showing more than 60% similarity. Only three AFLP bands were shared by both short-and long-spored strains, whereas 39% of the bands were shared with Vd strains isolated from noncrucifer hosts.

The genetic diversity of populations of Verticillium spp. has also been studied using sequences of the intergenic spacer region of the ribosomal DNA (IGS rDNA), which evolves rapidly. Conversely, the internal transcribed spacer (ITS rDNA) and six nuclear and one mitochondrial genes failed to differentiate the strains from Verticillium spp [START_REF] Klosterman | Diversity, Pathogenicity, and Management of Verticillium Species[END_REF].

Symptoms of Verticillium disease

Because Verticillium symptoms can vary between hosts, there are no unique symptoms that belong to all plants infected by this fungus. Despite the name Verticillium wilt, true wilt not always occurs as a consequence of Verticillium infection. Typical wilting starts with disease symptoms only at one half of an infected leaf (Figure 3A), usually in the oldest shoots as invasion is acropetal (from base to apex). For tomato, lower leaves turn yellow as tips and edges die, causing typical V-shaped lesions (Figure 3B). Ultimately the whole leaf wilts and may abscise. Alternatively, leaves may develop yellow blotches that later turn necrotic and brown, and the veins may appear brown or purple. For several plant species, wilting of young shoots can occur during warmer periods of the day with recovery at night. Drought or other conditions that reduce the plant's vitality can bring out disease development and symptom expression. Annuals often survive the season, but may be chlorotic, stunted, early senescent (Figure 3C) and have smaller yield. In stem sections a brown discoloration of the vascular tissues can be seen (Figure 3D). Overall, Verticillium diseases are difficult to diagnose based on symptom expression, especially because several Fusarium species cause similar symptoms [START_REF] Fradin | Physiology and molecular aspects of Verticillium wilt diseases caused by V.dahliae and V.albo-atrum[END_REF]. Symptoms of Verticillium-wilt in naturally infected alfalfa plants in Iran are shown in Figure 4. dahliae on necrotic stem tissue of tomato [START_REF] Fradin | Physiology and molecular aspects of Verticillium wilt diseases caused by V.dahliae and V.albo-atrum[END_REF].

Figure 4

Symptoms of Verticillium-wilt in naturally infected alfalfa plants from Markazi Province, Iran: the wilting of aerial parts and vascular browning typically associated with infection by Verticillium (left: infected plant; right: uninfected) [START_REF] Ghalandar | Verticillium wilt (Verticillium albo-atrum) on Medicago sativa (alfalfa) in Iran[END_REF].

The Verticillium disease cycle

V. dahliae and V. albo-atrum are soil-borne vascular fungi that attack plants through the roots.

V. dahliae causes monocyclic disease, meaning that only one cycle of disease and inoculums production occurs during a growing season. In contrast to V. dahliae, V. albo-atrum may produce conidia on infected plant tissues that become airborne and contribute to spread of the disease. Therefore, the diseases caused by V. albo-atrum can sometimes be polycyclic [START_REF] Fradin | Physiology and molecular aspects of Verticillium wilt diseases caused by V.dahliae and V.albo-atrum[END_REF].

The life cycle of both species is very similar and can be divided into a dormant, a parasitic and a saprophytic phase (Figure 5). In the dormant phase, germination of fungal resting structures present in the soil is inhibited through microbiostasis or mycostasis, which is overcome probably by the availability of excess carbon and nitrogen in root exudates released in the rhizosphere of host and non-host plants [START_REF] Fradin | Physiology and molecular aspects of Verticillium wilt diseases caused by V.dahliae and V.albo-atrum[END_REF]. As each individual cell of a microsclerotium has the ability to germinate once, a microsclerotium can germinate multiple times, which increases the chance of establishing a successful infection.

Hyphae that grow out of the germinating resting structures can traverse a limited distance, possibly directed by nutrient gradients, to reach potential host plants. It has been calculated

that the sphere of influence of the root on V. dahliae is likely to be 300 µm or less. Typically, Verticillium spp. enter their parasitic stage by infecting susceptible plants either at the root tip or at the sites of lateral root formation. To traverse into the vascular (xylem) tissues, the fungus needs to cross the endodermis which acts as a physical barrier against infection.

Therefore, crossing the endodermis may only be achieved when it has not yet developed (at the root tip) or when it is damaged (for instance by nematode infection) [START_REF] Fradin | Physiology and molecular aspects of Verticillium wilt diseases caused by V.dahliae and V.albo-atrum[END_REF]. After crossing the endodermis, the fungus enters the vascular tissues where it can form conidia, a process referred to as budding. These conidia are carried with the sap stream and trapped in pit cavities or at vessel end walls, so-called trapping sites, where they have to germinate and penetrate adjacent vessel elements in order to continue colonization.

Sporulation then occurs to start another infection cycle. It has been demonstrated that the rate of conidiation in planta correlates with the aggressiveness of the strain, with heavily conidiating Verticillium strains being more aggressive. In several studies it has been determined that it takes between 2 and 4 days before the fungus enters the xylem vessels of the root and another day to spread to neighbouring xylem elements and to sporulate. The initial sporulation in the root is thought to account for colonization of stem vessels, which results in rapid accumulation of fungal biomass a few days later. At that time (around 1 week after inoculation) the first fungal elimination occurs, which the pathogen on a susceptible plant is able to overcome subsequently [START_REF] Fradin | Physiology and molecular aspects of Verticillium wilt diseases caused by V.dahliae and V.albo-atrum[END_REF]. It has been reported that colonization of the plant at this stage appears to occur in cycles of fungal proliferation and fungal elimination, with elimination probably driven by plant defence responses. During tissue necrosis or plant senescence the fungus enters a saprophytic stage. Apart from the vascular tissues, shoots and roots of the plant now also become colonized. At this stage V.

albo-atrum can produce its conidia on infected plant tissues that may be dispersed by air currents and start another cycle of disease. In V. dahliae infection, large amounts of microsclerotia are produced (Figure 3E). These are released in the soil with the decomposition of plant materials where they can survive for 10-15 years. The survival potential of the melanized, dark, resting mycelium produced by V. albo-atrum is shorter. In addition, both species can overwinter as mycelium within perennial hosts or in plant propagative organs such as tubers, bulbs or seeds [START_REF] Fradin | Physiology and molecular aspects of Verticillium wilt diseases caused by V.dahliae and V.albo-atrum[END_REF].

Figure 5

The life cycle of V. dahliae and V. albo-atrum [START_REF] Berlanger | Verticillium wilt. The Plant Health Instructor[END_REF].

Genetic variability for resistance to Verticillium disease

In several plant species, including alfalfa (Medicago sativa), cotton (Gossypium hirsutum), potato (Solanum tuberosum), strawberry (Fragaria vesca), sunflower (Helianthus annuus), and tomato, sources of genetic resistance to Verticillium have been described (reviewed in [START_REF] Fradin | Physiology and molecular aspects of Verticillium wilt diseases caused by V.dahliae and V.albo-atrum[END_REF][START_REF] Klosterman | Diversity, Pathogenicity, and Management of Verticillium Species[END_REF]. Most of these crop species contain genes for tolerance or partial resistance, but not complete resistance to the fungus [START_REF] Fradin | Physiology and molecular aspects of Verticillium wilt diseases caused by V.dahliae and V.albo-atrum[END_REF]. The tomato is an exception in which resistance to race 1 of Verticillium isolates is conferred by a single dominant locus that was introduced in cultivated varieties in the 1950s [START_REF] Schaible | Inheritance of resistance to Verticillium wilt in a tomato cross[END_REF][START_REF] Diwnan | Mapping of Ve in tomato: a gene conferring resistance to the broad-spectrum pathogen Verticillium dahliae race 1[END_REF] and that is still carried by most commercial tomato varieties. This locus, known as Ve, comprises two closely linked inversely oriented genes, Ve1 and Ve2; [START_REF] Fradin | Genetic Dissection of Verticillium wilt Resistance mediated by Tomato Ve11[C][W][OA[END_REF] demonstrated that solely Ve1 determines the resistance of the tomato toward race 1 strains of Verticillium. The successful inter-species transfer of R genes has been reported in many plant species (Thilmony et al., 1995;[START_REF] Seo | A viral resistance gene from common bean functions across plant families and is up-regulated in a non-virus specific manner[END_REF]. While there are examples that R genes are functional when transferred across family boundaries, they generally exhibit restricted taxonomic functionality (Tai et al., 1999), conferring a resistance response only in closely related species within a family. Given the close polygenic relationship between M. truncatula and alfalfa, functional R gene transfer in Medicago should not be a challenge [START_REF] Yang | Alfalfa benefits from Medicago truncatula: the RCT1 gene from M. truncatula confers broad-spectrum resistance to anthracnose in alfalfa[END_REF]. Studies on the genetic variation for resistance to Verticillium wilt in alfalfa indicate that existing resistance levels are still insufficient and should be improved through further selection [START_REF] Huang | Susceptibility of Chinese alfalfa cultivars to Verticillium wilt[END_REF][START_REF] Vandemark | Heritability of resistance to Verticillium wilt in alfalfa[END_REF]. Among 50 alfalfa varieties of a European reference collection, less than 10 were resistant to Vaa [START_REF] Molinéro-Demilly | Resistance to Verticillum albo-atrum in lucerne (Medicago sativa L.) to distinguish between varieties[END_REF]. Inheritance of alfalfa resistance to Vaa can be quantitative or qualitative, and distinct physiological features have been associated to these two forms of resistance (reviewed by [START_REF] Pennypacker | Differential impact of carbon assimilation on the expression of quantitative and qualitative resistance in alfalfa (Medicago sativa)[END_REF][START_REF] References Acharya | Breeding alfalfa for resistance to Verticillium wilt: a sound strategy[END_REF].

Principles in plant-pathogen interactions

Plant disease is the exception rather than the rule, as many plant pathogens express a virulent phenotype only on one or a limited number of host species. Pathogens inoculated onto a nonhost species either lack the ability to grow and infect that plant, or following ingress invariably encounter a successful resistance mechanism. Interaction with host species exhibit a range of specificities dependent on the strategy of the pathogen [START_REF] Lamb | Signals transduction mechanisms for activation of plant defenses against microbial attack[END_REF].

One type of pathogen is the unspecialized which is necrotrophic and damages the host through production of toxins and/or enzymes. This type is often equipped with inactivation or avoidance mechanisms to deal with host defenses. In contrast biotrophs avoid serious host damage at least in the early stages, and unlike necrotrophs do not activate host defenses nonspecifically. For specialized pathogens without avoidance mechanisms, host defenses, if induced, are usually effective. In these specific interactions, following attempted infection by the pathogen, molecular signals determine whether the interaction will be incompatible or compatible. In an incompatible interaction (host resistant, pathogen avirulent) early molecular recognition is followed by rapid expression of defense responses. In a compatible interaction (host susceptible, pathogen virulent) the pathogen eludes the plant's surveillance mechanisms and disease ensues [START_REF] Lamb | Signals transduction mechanisms for activation of plant defenses against microbial attack[END_REF].

Non host interaction

Resistance shown by an entire plant species to a specific parasite or pathogen is known as non host resistance, and is expressed by every plant towards the majority of potentially pathogenic microbes. Non host resistance, therefore, is the most common form of disease resistance exhibited by plants. Non host resistance to fungi, at least, generally seems be under complex genetic control and can involve a multiplicity of defense factors that, individually, may segregate within the species without compromising overall resistance. Such resistance contrasts with host resistance, which is expressed by plant genotypes within an otherwise susceptible host species [START_REF] Heath | Non-host resistance nonspecific plant defenses[END_REF].

Despite the recent focus on inducible defensive responses in plants, there is considerable evidence that preformed defenses are a major component of non host resistance, particularly in non-domesticated plants [START_REF] Heath | Non-host resistance nonspecific plant defenses[END_REF][START_REF] Kamoun | Nonhost resistance to Phytophthora: novel prospects for a classical problem[END_REF].

For fungal pathogens that attempt to penetrate cells, recent data support the idea that highly localized responses within the cell wall and early signaling events play a primary role in nonhost resistance [START_REF] Heath | Non-host resistance nonspecific plant defenses[END_REF].

Incompatible host interaction

The appearance of cell death at the site where attempeted attack has been done by the pathogen (the hypersensitive response or HR) is a characteristic feature of resistance in plants. When the pathogen is specifically recognized by a plant in a process of 'incompatible' interaction this response happens. The HR is followed by many defense mechanisms in neighboring cells and an implication of this response is the beginning of systemic acquired resistance (SAR). Quickly tissue collapsing is a manifestation of the cell death. Some characteristic morphological features, which are common in animal apoptosis but are not found in all pathosystems, shown by this cell death are membrane blebbing, nucleus condensation, , production of structures reminiscent of apoptotic bodies, fragmentation of the DNA, mitochondrial swelling and shrinkage of the cell. Another feature of disease symptoms which happens very late in the process of infection during a 'compatible' interaction is cell death. [START_REF] Pontier | The hypersensitive response. A programmed cell death associated with plant resistance[END_REF].

Compatible host interaction

This interaction occurs between a susceptible or intermediate resistant host and a virulent pathogen. In this interaction product of virulent gene is not recognized by product of resistance gene of plant, as a result pathogen can infect plant. But plant can active certain defense mechanisms because of production of MAMPs (Microb-Associated Molecular Patterns) by pathogen. Defense response can change the degree of susceptibility host and it has much correlation to quantitative resistance [START_REF] Pontier | The hypersensitive response. A programmed cell death associated with plant resistance[END_REF].

Type of defense mechanisms

Preexisting defense structures

The structure of a plant is the first line of defense against pathogens, and if the pathogen wants to cause infection it must stick to and penetrate the plant surface. The plant enjoys some structural defenses even before the pathogen has any contact with the plant. Such structural defenses which are present in the plant are the amount and quality of wax and cuticle covering the epithermal cells, the structure of the epithermal cell walls, the size, location, and shapes of stomata and lenticles, and the presence of tissues made of thickwalled cells hindering the advance of the pathogen o the plant. A water repellent structure is formed by waxes in leaf and fruit, and this surface can prevent the formation of a water layer on which pathogens might be deposited and germinate (fungi) or multiply (bacteria). Also a similar water repelling effect may be exerted by a thick mat of hairs on a plant surface which may reduce infection [START_REF] Agrios | Plant pathology[END_REF].

An increase of resistance to infection in disease may be caused by a thick cuticle and the pathogen can enter its host only via direct penetration in this disease. However, cuticle thickness and resistance are not always correlated, and directly penetrating pathogens can easily invade many plant varieties with cuticles of considerable thickness [START_REF] Agrios | Plant pathology[END_REF].

Some apparently important factors for some plants to resist against certain pathogens include the thickness and toughness of the outer wall of epidermal cells. It is difficult or impossible for fumgal pathogens to make direct penetrateion when facing thick, tough walls of epidermal cells. Plants having such thick, tough walls are often resistant, but if the pathogen enters the epidermis of the same plant thtough a wound, the pathogen invade, the inner tissues of the plant easily. [START_REF] Agrios | Plant pathology[END_REF].

Preexisting chemical defenses

It is clear that the resistance of a plant against pathoge attacks depends more on the substances produced in its cells before or after infection than on its structural barriers, although a plant may be provided with various degrees of defense against attacking pathogens by structural charactersitics. This is an apparent fact that certain plant varieties will not be infected by certain pathogen although it seems that no structural barriers of any kind is to be present or to form in these varieties. Similarly, the rate of disease development soon slows down in resistant varieties, and finally, the disease is completely checked in the absence of structural defenses. In addition, many pathogens enter nonhost plants naturally or many of them are introduced in to nonhost plants artifically. In these cases, such pathogens cannot cause infection even though there are no apparent visible host structures to prevent them from doing so [START_REF] Agrios | Plant pathology[END_REF].

Induced structural defenses

Most pathogens can penetrate their host by means of wounds and natural openings and can produce various degrees of infection in spote of the performed superficial or internal defense structures of host plants. Even after the performed defense structure has been penetrated by the pathogen, however, the plants response is usually forming one or more types of structures that can defend the plant from further pathogen invasion more or less successfully. The cytoplasm of the attacked cells is involved in some of the formed defense structures, this process is called cytoplasmic defense reaction; others which are called cell wall defense structure involve the walls of invaded histological defense structure involved in the formation of cork layers, the information of abscission layers, the formation of tyloses, and deposition of gums involve tissues ahead of the pathogen (deeper in to the plant). Finally, the plant may be protected from further invasion by the death of the invaded cell. This process is named as the necrotic or hypersensitive defense reaction [START_REF] Agrios | Plant pathology[END_REF].

Effects of pathogens on plant physiological functions

When pathogens infect plants during the process of their gaining food for themselves, they interfere with the different physiological functions of the plant based on the type of pathogen and on the plant organ and tissue they infect, and this process leads to the development of different symptoms. Therefore, a pathogen infecting and killing the flowers of a plant interferes with the capability of the plant for producing seed and multiplying. A pathogen infecting and killing a part of or all of the root of a plant decreases the capability of the plant for absorbing water and nutrients, and this process results in its wilting and death. Similarly, a pathogen infecting and killing parts of the leaves and destroying their chlorophyll results in the reduced photosynthesis, growth, and yield of the plant, and so on. The relationship between the symptoms of the plant and the affected physiological functions is clear and understandable in most cases [START_REF] Agrios | Plant pathology[END_REF].

Effect of pathogens on the photosynthesis

Considering the essential position of photosynthesis in the plant life, it is obvious that any interference with photosynthesis caused by a pathogen leads to a diseased condition in the plant. The chlorosis the pathogens cause on many infected plants, the necrotic lesions or large necrotic areas they produce o green plant parts, and the reduced growth and amount of fruits produced by many infected plants are symptoms that pathogens interfere with photosynthesis.

In cases of leaf spot, blight, rusts, fungal leaf spots, and other kinds of diseases the photosynthesis is reduced because of a decrease in the photosynthetic surface of the plant [START_REF] Agrios | Plant pathology[END_REF].

The capture and storage of visible light energy in leaves of higher plants is mediated by an intricate association between light-harvesting pigment-protein complexes and sequential electron transport from PSII to PSI. The efficiency of utilization of light by each of the photosystems varies in coordination with the capacity of the C0,-fixing reactions to consume NADPH and ATP generated by the light reactions [START_REF] Foyer | The mechanisms contributing to photosynthetic control of electron transport by carbon assimilation in leaves[END_REF]. In particular, patterns of energy use in PSII with changing irradiance and other environmental conditions have been revealed by Chlorophyll fluorescence [START_REF] Papageorgiou | Chlorophyll fluorescence: an intrinsic probe of photosynthesis[END_REF][START_REF] Krause | Chlorophyll fluorescence and photosynthesis: the basics[END_REF].

Chlorophyll fluorescence is a non-destructive, rapid indicator of photosynthetic efficiency, and a good tool for early detection of stress effects on plants [START_REF] Schreiber | Chlorophyll fluorescence as a nonintrusive indicator for rapid assessment of in vivo photosynthesis[END_REF]. One of the early symptoms of wilt disease is the reduction in the rate of photosynthesis [START_REF] Bowden | Mechanism of photosynthesis decrease by Verticillium dahliae in potato[END_REF]. The Fv/Fm ratio (a measure of maximal quantum efficiency of PS II) was showed as an indicator of tolerance, which can be easily applied to individual plants [START_REF] Maxwell | Chlorophyll fluorescence-a practical guide[END_REF][START_REF] Smethurst | Screening methods for water logging tolerance in lucerne: Comparative analysis of water logging effects on chlorophyll fluorescence, photosynthesis, biomass and chlorophyll content[END_REF]. [START_REF] Floerl | Disease symptoms and mineral nutrition in Arabidopsis Thaliana response to Verticillium Longisporum VL43 infection[END_REF] infected Arabidopsis thaliana with Verticillium longisporu VL43, results showed that the leaves of VL43-infected plants showed reduced chlorophyll content (-20%) but only marginal effects on photosynthetic electron transport of PS II (-2%) compared with controls. Chlorophyll fluorescence characteristics of cotton leaves under disease stress were studied. The results

showed that the chlorophyll fluorescence parameters of Fv, Fm, Fv/Fm, Fv/Fo, Fm/Fo, ΦPSII were all decreased, but Fo increased with increasing severity level (SL) of disease [START_REF] Bing | The effects of disease stress on spectra reflectance and chlorophyll fluorescence characteristics of cotton leaves[END_REF]. Chlorophyll content and some parameters like Fv / Fm, Fv / Fo and Yield in leaves of virus-free plantlets for chewing cane (Badila) that was treated with hot-water and planted in greenhouse were measured. The results showed that those of were higher than those without hot-water treatment. Therefore through virus-free treatment, the chlorophyll content in leaves of chewing cane and photosynthetic efficiency was increased and would be good to promote the photosynthesis (Cheng-mei1 et al., 2009).

Effect of pathogens on plant growth

It is simply understood and expected that the pathogens destroying part of photosynthetic area of plants and significantly reducing photosynthetic output often leads to smaller growth of these plants and smaller yields. Similarly, the pathogens destroying part of the roots of a plant or clogging their xylem or phloem elements, thereby severely interfering with the translocation of water and of inorganic or organic nutrients in these plants, often reduce the size and yields of these plants and sometimes cause them to die [START_REF] Agrios | Plant pathology[END_REF].

Effect of pathogens on plant reproduction

Pathogens attacking various organs and tissues of plants weaken and often kill these organs or tissues, and this process weakens the plants. Therefore, these plants are smaller in size, may generate fewer flowers, and may yield fewer fruit and seeds; these seeds may have inferior vigor and vitality and, therefore, if planted, they may generate fewer and weaker plants. Besides these indirect effects of pathogens on plant reproduction, many plants also have a direct adverse effect on plant reproduction because of their attacking and killing the flowers, fruit, or seed directly, or their interfering and inhibiting plant production, or their interfering directly or indirectly with the propagation of their host plant [START_REF] Agrios | Plant pathology[END_REF].

The genetics of resistance

There are two different types of genetically determined resistance:

• The qualitative resistance, also called race-specific, monogenic or vertical resistance, which is based on a gene-for-gene relationship. The resistance phenomenon is the result of an incompatible reaction, due to the interaction between the plant resistance gene and the pathogen virulence gene when they are both in the dominant form (R-Avr). If at least one of these genes is in the recessive form (R-avr, r-Avr and r-avr), the compatible reaction takes place and the plants shows its susceptibility to the pathogen (Table 1). Such resistance differentiates clearly between races of a pathogen, as it is effective against specific races of the pathogen and ineffective against others [START_REF] Agrios | Plant pathology[END_REF].

Table 1 Quadratic check of gene combinations and disease reaction types in a host-pathogen system in which the gene-for-gene concept for one gene operates. The minus sign indicates incompatible (resistant) reactions and therefore no infection; the plus sign indicates compatible (susceptible) reactions and therefore the infection develops [START_REF] Agrios | Plant pathology[END_REF].

• The quantitative resistance, also called partial, polygenic or horizontal resistance, which is controlled by several genes. All plants have a certain, but not always equal, level of possibly unspecific resistance that is effective against each of their pathogens.

In other words, it appears in a range of tolerances depending on the alleles combination of the genes involved in the resistance [START_REF] Agrios | Plant pathology[END_REF]. Varieties with qualitative resistance generally show complete resistance to a specific pathogen under most environmental conditions, but a single or few mutations in the pathogen may produce a new race that may infect the previously resistant variety. On the contrary, varieties with quantitative resistance are less stable and may vary in their reaction to the pathogen under different environmental conditions, but a pathogen will have to undergo many more mutations to completely break down the resistance of the host [START_REF] Agrios | Plant pathology[END_REF]..

Resistance or susceptibility genes in the plants

The host range of several pathogenic fungi has been described to evolve due to horizontal gene flow between strains and species [START_REF] Mehrabi | Horizontal gene and chromosome transfer in plant pathogenic fungi affecting host range[END_REF]. Monogenic resistance is easy to manipulate in a breeding program, and therefore is often preferred to polygenic resistance;

however, the research for quantitative resistance leads to a more durable protection of the plant [START_REF] Agrios | Plant pathology[END_REF].

The interaction of M. truncatula with pathogenic microorganisms

Medicago truncatula has been studied intensely with regard to the symbiotic interaction with Rizobia but it is also a model to study pathogen resistance mechanisms [START_REF] Ray | Medicago truncatula as a model for understanding plant interactions with other organisms, plant development and stress biology: past, present and future[END_REF].

M. truncatula is host to some nematodes. After hatching in the soil, root-knot nematodes must locate and penetrate a root, migrate into the vascular cylinder, and establish a permanent feeding site. Presumably, these events are accompanied by extensive signaling between the nematode parasite and M. truncatula. Remarkably, plant-parasitic root-knot nematodes (RKN) invoke a cytoskeletal response identical to that seen in response to Nod factors (NF)

and induce root-hair waviness and branching in legume root hairs via a signal able to function at a distance [START_REF] Bird | Signaling between nematodes and plants[END_REF][START_REF] Weerasinghe | Root-knot nematodes and bacteria Nod factors elicit common signal transduction events in Lotus japonicus[END_REF].

Resistance genes were detected in the interaction between M. truncatula with some aphid species. One major locus, RAP1, was identified that was sufficient to confer race-specific resistance against the pea aphid and was mapped to the middle of chromosome 3.

Surprisingly, a separate locus, mapping to the top of chromosome 3, governed aphid induced HR, indicating that the HR-like lesions are not required for RAP1-mediated aphid resistance.

By 8 weeks after sowing, when plants were sampled for aphid numbers, a pronounced difference in plant damage was observed between Jester and Jemalong, with mean damage scores of 2.3 and 9.8, respectively (Klinger et al., 2005;Stewart et al., 2009).

Interactions between M. truncatula with several fungi were demonstrated, such as the leaf fungus Colletotrichum trifolii [START_REF] Torregrosa | Cytological, genetic, and molecular analysis to characterize compatible and incompatible interactions between Medicago truncatula and Colletotrichum trifolii[END_REF], the causal agent of anthracnose on Medicago sativa. Screening of a few M. truncatula lines identified Jemalong A17 and F83005.5 as resistant and susceptible to Colletotrichum trifolii race 1, respectively. Symptom analysis and cytological studies indicated that resistance of Jemalong was associated with a hypersensitive response of the plant. Examination of the disease phenotypes indicated that resistance was dominant and was probably due to a major resistance gene. A major QTL for resistance to two races was reported on chromosome 4 [START_REF] Torregrosa | Cytological, genetic, and molecular analysis to characterize compatible and incompatible interactions between Medicago truncatula and Colletotrichum trifolii[END_REF][START_REF] Yang | Alfalfa benefits from Medicago truncatula: the RCT1 gene from M. truncatula confers broad-spectrum resistance to anthracnose in alfalfa[END_REF]. M. truncatula is also a useful pathosystem for root diseases caused by Ralstonia solanacearum [START_REF] Vailleau | Characterization of the interaction between the bacterial wilt pathogen Ralstonia solanacearum and the model legume plant Medicago truncatula[END_REF]. The soilborne pathogen Ralstonia solanacearum is the causal agent of bacterial wilt and attacks more than 200 plant species, including some 2010). Among eight tested M. truncatula lines, all were susceptible to F. oxysporum f.sp. medicaginis, the causal agent of Fusarium wilt in alfalfa. However, a tolerant line, F83005.5, and a susceptible line, A17, could be distinguished by scoring the disease index.

The interaction between M. truncatula and other pathogens was reported, such as Phoma medicaginis [START_REF] Ellwood | Identification of Sources of Resistance to Phoma medicaginis isolates in Medicago truncatula SARDI Core Collection Accession, and Multigene Differentiation of Isolates[END_REF] and Pseudomonas syringe. (Bozso et al., 2009) . Table 2 summarises interactions between Medicago truncatula and pathogenic microorganisms.

A17 and F83005.5 genotypes of M. truncatula are often contrasting in their response to pathogens, and are widely used to study differential defense responses to pathogens [START_REF] Torregrosa | Cytological, genetic, and molecular analysis to characterize compatible and incompatible interactions between Medicago truncatula and Colletotrichum trifolii[END_REF]Ramirez-Suero et al., 2010;[START_REF] Jaulneau | Host and non host resistance in Medicago-Colletotrichum interactions[END_REF].

QTL: Quantitative Trait Loci

A major area of study in genetics has been quantitative characters for over a century, since they are regarded as a common feature of natural variation in population of all eukaryotes including crop plants. Traits exhibiting continuous variation are termed quantitative traits.

Continuous variation is caused by two factors: simultaneous segregation of many genes affecting the trait and/or environment influencing on the expression of the trait [START_REF] Falconer | Introduction to Quantitative Genetics 4th edition[END_REF]. In crop plants most traits of economical importance, including yield, earliness, height and many quality traits, drought and some forms of disease resistance are controlled by many genes and are known as quantitative traits (also polygenic, multifactorial or complex traits). QTL (Quantitative Trait Loci), a term first coined by [START_REF] Geldermann | Investigations on inheritance of quantitative characters in animals by gene markers I[END_REF].

The regions within genomes that contain genes associated with a particular quantitative trait are known as QTLs.

Conceptually, a QTL can be a single gene, or it may be a cluster of linked genes that affect the trait. The procedures for finding and locating the quantitative trait loci (QTLs) and analyzing their magnitude of genetic effects and interactions with environment are called QTL mapping.

In the past 20 years there has been a remarkable increase in the use of QTL mapping as a tool to uncover the genetic control of traits. Studies of QTL mapping have been reported in most crop plants for divers traits including yield, quality, disease and insect resistance, abiotic stress tolerance, and environmental adaptation.

QTL mapping requires the construction of a linkage map population using a cross between phenotypically divergent accessions. In the offspring of such a cross, association between a trait and marker alleles arises from linkage between marker loci and trait. By identifying these associations, the method allows the location of genomic regions on a marker linkage map that most likely contain genes involved in the trait. The results of QTL mapping provide the most likely position of the QTL, together with an estimate of the allele substitution effects (the additive effect) and so called "supportive intervals" that roughly correspond to confidence intervals for the QTL map positions. The vast majority of molecular marker research in quantitative traits has been devoted to mapping QTL. These experiments basically have the following major objectives: To identify the regions of the genome that affect the trait of interest and to analyze the effect of the QTL on the trait.

Molecular markers

Since the discovery of the primary structure of DNA, it has been characterized in a number of species. Many molecular marker detection systems that have the ability to distinguish variation present in genomic DNA sequences have been developed for genetic analysis.

Molecular markers are now widely used to track loci and genome regions in several cropbreeding programmes, as molecular markers are tightly linked with a large number of agronomic and disease resistance traits in major crop species [START_REF] Phillips | DNA-based markers in plants[END_REF][START_REF] Jain | Molecular techniques in crop improvement[END_REF][START_REF] Gupta | Cereal genomics: an overview Gupta[END_REF]. These molecular markers include:

SSR-markers

Simple sequence repeat (SSR) (Tautz, 1989) also called microsatellite, is one of the most important categories of molecular markers. It comprises the core marker system of the PCR based molecular markers and is widely used for DNA fingerprinting, genetic mapping, MAS and studies of genetic diversity and population genetics [START_REF] Hearne | Microsatellites for linkage analysis of genetic traits[END_REF]. SSRs are stretches of DNA consisting of tandemly repeated short units of 1-6 basepairs in length, and are codominantly inherited [START_REF] Johansson | Cloning and characterization of highly polymorphic porcine microsatellites[END_REF]. Such motifs are abundant and highly polymorphic in the genome of eukaryotes [START_REF] Tóth | Microsatellites in different eukaryotic genomes[END_REF]. Microsatellites can be found anywhere in the genome, both in protein-coding and noncoding regions. The conserved sequences in the flanking regions of simple sequence repeats can be designed as a pair of specific primers to detect the DNA length polymorphism via the polymerase chain reaction [START_REF] Litt | A hypervariable microsatellite revealed by in vitro mpilification of a dinucleotide repeat within the cardiac muscle actin gene[END_REF][START_REF] Weber | Abundant class of human DNA polymorphism which can be typed using the polymerase chain reaction[END_REF]. A high level of polymorphism is to be expected because of the proposed mechanism responsible for generating SSR allelic diversity by replication slippage (Tautz et al., 1986). The SSR markers can be identified by sequencing microsatellite-containing clones isolated from small-insert genomic DNA libraries via hybridization with synthetic oligonucleotide probes, a method which is time-consuming and relatively expensive. A low cost way of SSRs development is screening of sequences in the public database.

The most frequently found repetitive motifs of mono-, di-, tri-, or tetranucleotide units are (A)n, (GA)n, (TAT)n and (GATA)n in plants [START_REF] De Vienne | Principal sources of molecular markers In:Molecular markers in plant genetics and biotechnology[END_REF]. The most abundant dimeric microsatellite in several well-known mammals is the AC repeat [START_REF] Beckmann | Survey of human and rat microsatellites[END_REF], while in many plant species they are AT or GA repeat [START_REF] Wang | Survey of plant short tandem DNA repeats[END_REF].

More than 75% of the barley genome comprises repetitive DNA sequences [START_REF] Flavell | Repeated sequence DNA relationships in four cereal genomes[END_REF]. It is estimated that the barley genome contains one GA repeat every 330kb and one GT repeat every 620kb (Liu et al., 1996b). Similar results were obtained with other important crops, such as wheat [START_REF] Plaschke | Detection of genetic diversity in closely related bread wheat using microsatellite markers[END_REF][START_REF] Röder | Abundance, variability and chromosmal location of microsatellites in wheat[END_REF], rice [START_REF] Wu | Abundance, polymorphism and genetic mapping of microsatellites in rice[END_REF], and maize [START_REF] Gupta | The development and use of microsatellite markers for genetic analysis and plant breeding with emphasison bread wheat[END_REF]. Among trinucleotide repeats in barley, (CCG) n, (AGG) n and (AGC) n repeats are the most-frequent motifs while (ACGT) n and (ACAT) n in tetrameric microsatellites (Thiel et al., 2003). The discovery of microsatellites has significantly increased the marker density of linkage maps for some mammals, human [START_REF] Engelstein | A PCR based linkage map of human chromosome 1[END_REF][START_REF] Dib | A comprehensive genetic map of the human genome based on 5,264 microsatellites[END_REF] and mouse [START_REF] Dietrich | A comprehensive genetic map of the mouse genome[END_REF]. Molecular linkage maps in many model plants and crops were improved rapidly by the addition of SSR markers, such as in Arabidopsis [START_REF] Bell | Assignment of 30 microsatellite loci to the linkage map of Arabidopsis[END_REF], rice [START_REF] Mccouch | Microsatellite marker development, mapping and applications in rice genetics and breeding[END_REF], wheat [START_REF] Röder | A microsatellite map of wheat[END_REF] and maize [START_REF] Senior | Mapping maize microsatellites and polymerase chain reaction confirmation of the targeted repeats a CT primer[END_REF]. The informative value of microsatellite markers for genetic studies and as a powerful tool for barley breeding was confirmed in several studies [START_REF] Maroof | Extraordinarily polymorphic microsatellite DNA in barley-species diversity, chromosomal locations, and population dynamics[END_REF][START_REF] Becker | Barley microsatellites: allele variation and mapping[END_REF]Liu et al., 1996b;Struss and Plieske, 1998). Among several important DNA marker systems, SSR markers showed the highest polymorphism, followed by RFLPs, RAPDs and AFLPs [START_REF] Russell | Direct comparison of levels of genetic variation among barley accessions detected by RFLPs, AFLPs, SSRs and RAPDs[END_REF]. A second-generation linkage map of barley using only PCR-based microsatellite markers was constructed [START_REF] Ramsay | A simple sequence repeat-based linkage map of barley[END_REF]. Besides microsatellites derived from genomic clones, also

ESTs were exploited for the development of PCR-based SSR-markers (Thiel et al., 2003;[START_REF] Pillen | Mapping new EMBL-derived barley microsatellites and their use in differentiating German barley cultivars[END_REF][START_REF] Holton | Identification and mapping of polymorphic SSR markers from expressed sequences of barley and wheat[END_REF].

Statistical Methods for QTL Mapping

Undoubtedly, the development of statistical methods has played an important role for the detection of the association between DNA markers and quantitative characters. The first report of an association between a morphological marker and a quantitative trait was reported by [START_REF] Sax | The association of size difference with seed-coat pattern and pigmentation in Phaselous vulgaris[END_REF].

QTL mapping programs can be roughly classified into different groups according to the number of markers or genetic models and analytical approaches applied [START_REF] Liu | Computational tools for study of complex traits In: Molecular Dissection of Complex Traits by Paterson AH[END_REF][START_REF] Hoeschele | Advances in statistical methods to map quantitative trait loci in outbred populations[END_REF]. According to the number of markers, single-QTL models and multiple-locus models can be classified [START_REF] Liu | Computational tools for study of complex traits In: Molecular Dissection of Complex Traits by Paterson AH[END_REF]. According to the analytical technology, the methods can be grouped into one-way ANOVA or simple t-test, simple linear regression, multiple linear regression, nonlinear regression, log-linear regression, likelihood functions, MCMC (Markoff Chain Monte Carlo), mixed linear models, and Bayesian approach [START_REF] Wang | Mapping QTLs with epistatic effects and QTL-environment interactions by mixed linear model approaches[END_REF].

Briefly, the statistical analyses of associations between phenotype and genotype in a population to detect QTLs include single-marker mapping (Luo and Kearsey, 1989), interval mapping [START_REF] Lander | Mapping mendelian factors underlying quantitative traits using RFLP linkage maps[END_REF], and composite interval mapping (CIM) (Zeng, 1994), plus multiple traits mapping [START_REF] Jiang | Multiple trait analysis of genetic mapping for quantitative trait loci[END_REF][START_REF] Ronin | Linkage between loci of quantitative traits and marker loci: multi-trait analysis with a single marker[END_REF] as follow:

Single-marker tests

The simplest method for QTL mapping is single-marker mapping, including t-test, and analysis of variance (ANOVA) and simple linear regression, which assess the segregation of a phenotype with respect to a marker genotype [START_REF] Soller | The molecular genetic linkage map of the model legume Medicago truncatula: an essential tool for comparative legume genomics and the isolation of agronomically important genes[END_REF]. According to this principle progeny classified by marker genotype and compare phenotypic mean between classes (t-test or ANOVA). A significant difference indicates that a marker is linked to a QTL. The difference between the phenotypic means provides an estimate of the QTL effect. This approach can indicate which markers linked to potential QTLs are significantly associated with the quantitative trait investigated. In short, QTL location is indicated only by looking at which markers give the greatest differences between genotype group averages. Depending on the density of markers, the apparent QTL effect at a given marker may be smaller than the true QTL effect as a result of recombination between the marker and the QTL. The advantage of this method is a simple procedure that can be accomplished by a standard statistical analysis software package, such as SAS and Minitab. In contrast, the main weakness of single-marker tests is the failure to provide an accurate estimate of QTL location or recombination frequency between the marker and the QTL because the evaluation of individual markers is independently, and without reference to their position or order [START_REF] Doerge | Mapping and analysis of quantitative trait loci in experimental populations[END_REF].

Simple interval mapping (SIM)

Interval mapping is probably the most familiar method of QTL analysis. The introduction of interval mapping offered a new strategy to discern weak effects from genetic distance between marker locus and putative QTL using the power of a complete genetic map. The interval that is defined by ordered pairs of markers are searched in increments, and statistical methods are used to test whether a QTL is likely to be present at the location within the intervals or not. The principle behind interval mapping is to test a model for the presence of a QTL at many positions between two mapped marker loci. The model is fit, and its goodness is tested using the method of maximum likelihood. If it is assumed that a QTL is located between two markers, the 2-locus marker genotypes contain mixtures of QTL genotypes each. Maximum likelihood involves searching for QTL parameters that give the best approximation for quantitative trait distributions that are observed for each marker class.

Models are evaluated by computing the likelihood of the observed distributions with and without fitting a QTL effect. The LOD (logarithm of the odds) score is the log of the ratio between the null hypothesis (no QTL) and the alternative hypothesis (QTL at the testing position). Large LOD scores correspond to greater evidence for the presence of a QTL. The best estimate of the location of the QTLs is given by the chromosomal location that corresponds to the highest significant likelihood ratio. The LOD score is calculated at each position of the genome. In the case of many missing genotypes and large gaps on the map, the missing data are replaced by probabilities estimated from the nearest flanking markers [START_REF] Broman | Review of statistical methods for QTL mapping in experimental crosses[END_REF]. Until now, many software packages based on interval mapping were developed for QTL mapping, such as MAPMAKER/QTL and QGene. In comparison to single marker mapping, the benefits of these programs are a curve available across the genetic map indicating the evidence of QTL location and which allows the inference of QTLs to positions or gaps between two markers in order to make proper analysis for incomplete marker genotype data. Meanwhile, analysis can be used for testing the presence of genotyping errors [START_REF] Broman | Review of statistical methods for QTL mapping in experimental crosses[END_REF].

Composite interval mapping (CIM)

There are two problems with single interval mapping (SIM) method as a result from single QTL model mentioned above. One is that the effects of additional QTL will contribute to sampling variance. The other is that combined effects of two linked QTLs will cause biased estimates. The ideal solution would be to fit a model that contains the effects of all QTL.

However, the tremendous number of potential QTL and their interactions will lead to innumerable statistical models and heavy computational demands as using statistical approaches to locate multiple QTL. To deal with the this problem, several key papers were published [START_REF] Jansen | High resolution of quantitative traits into multiple loci via interval mapping[END_REF]. The approach of composite interval mapping assesses the probability that an interval between two markers is associated with a QTL that affects the trait of interest, and is as well controlling for the effects of other background markers on the trait. In theory, CIM gives more power and precision than SIM because the effects of other QTL are not present as residual variance. Furthermore, CIM can remove the bias that would normally be caused by QTL that are linked to the position being tested. The key problem with CIM concerns the choice of suitable background markers to serve as covariates.

QTL by environment interaction

Genotype by environment (QE) interaction is a common phenomenon for expression of quantitative traits. QE interaction has been demonstrated by classical genetics studies and has been of great concern for plant breeding programs [START_REF] Westcott | Some methods of analysing genotype-environment interaction[END_REF].

QTL mapping offer the opportunity to trace genotype by environment interactions between individual QTLs and environments. Reports about inconsistency in detection of QTLs across different environments are numerous. In contrast, Stuber et al., (1992) reported that QTL detection was relatively consistent across diverse environments. The difference in observations may be a function of the traits studied and may also be a function of the methods of identifying genotype by environment interaction. In most previous mapping reports, possible QTL x environment interactions were analyzed by comparing the QTLs detected separately in each environment or using the mean value of all environments. It was suggested that a QTL detected in one environment but not in another might indicate QTL x environment interaction. However, even in the absence of true QTL by environment interaction, a QTL can be detected in one environment but not in another, because the chance of simultaneous detection in both environments is naturally small. On the other hand, consistency in detection of QTLs at different environments may not conclusively indicate the absence of QTL x environment interaction. Recently, some methods have been proposed for dealing with QE interactions [START_REF] Piepho | A mixed-model approach to mapping Quantitative Trait Loci in barley on the basis of multiple environment data[END_REF].

QTLs detected in M. truncatula and some other plants for resistance to pathogenic microorganisms

Examples of phenotype mapping in M. truncatula range from disease resistance genes to quantitative trait loci (QTL) for morphology, development, and metabolism. Resistance against Colletotrichum trifolii (anthracnose) (Ameline- Torregrosa et al., 2008;[START_REF] Yang | Alfalfa benefits from Medicago truncatula: the RCT1 gene from M. truncatula confers broad-spectrum resistance to anthracnose in alfalfa[END_REF], Phoma medicaginis (black stem and leaf spot) [START_REF] Kamphuis | Two alternative recessive quantitative trait loci influence resistance to spring black stem and leaf spot in Medicago truncatula[END_REF], and Erysiphe pisi (powdery mildew) (Ameline- Torregrosa et al., 2008) have all been mapped in M.

truncatula. Some of these resistance loci have been positioned at high resolution and candidate nucleotide binding site-leucine rich repeat (NBS-LRR) gene sequences described (Ameline- Torregrosa et al., 2008 ;[START_REF] Yang | Alfalfa benefits from Medicago truncatula: the RCT1 gene from M. truncatula confers broad-spectrum resistance to anthracnose in alfalfa[END_REF]. A17 genotype of M. truncatula is reported to be resistant to Aphanomyces euteiches [START_REF] Djebali | Partial resistance of Medicago truncatula to Aphanomyces euteiches is associated with protection of the root stele and is controlled by a major QTL rich in proteasome-related genes[END_REF] to Colletotrichum trifolii and Erysiphe pisi (Ameline- Torregrosa et al., 2008), but susceptible to Fusarium oxysporum (Ramirez-Suero et al., 2010) and Ralstonia solanacearum [START_REF] Vailleau | Characterization of the interaction between the bacterial wilt pathogen Ralstonia solanacearum and the model legume plant Medicago truncatula[END_REF], whereas F83005.5 genotype of M. truncatula is susceptible to A. euteiches and C. trifolii and resistant to F. oxysporum and R. solanacearum.

Derived recombinant inbred lines from a cross between A17 and F83005.5 in Medicago truncatula were used for identification of QTLs involved in resistance to A.

euteiches and Ralstonia solanacearum, respectively (Djébali et al., 2009;[START_REF] Vailleau | Characterization of the interaction between the bacterial wilt pathogen Ralstonia solanacearum and the model legume plant Medicago truncatula[END_REF]. Two F2 populations of M. truncatula segregating for resistance to spring black stem were established between SA27063 resistant and two susceptible accessions, A17 and SA3054. In the SA27063 x A17 F2 population a highly significant QTL was mapped to the top arm of linkage group 4. Whereas the second QTL was located on the lower arm of LG8 in the SA27063 x SA3054 linkage map [START_REF] Kamphuis | Two alternative recessive quantitative trait loci influence resistance to spring black stem and leaf spot in Medicago truncatula[END_REF]. A molecular map of the F2 population derived from the interspecific cross of a highly tolerant Gossypium barbadense and a susceptible G. hirsutum was used to detect three QTLs with a large effect on resistance to Verticillium wilt [START_REF] Bolek | Mapping of Verticillium wilt resistance genes in cotton[END_REF]. QTLs were also detected for disease resistance in other pathosystems, such as chickpea-Ascochyta rabiei [START_REF] Ali | Detection of QTLs for blight resistance in chickpea genotypes with DNA based markers[END_REF], potato-Phytophthora infestans [START_REF] Bormann | Tagging Quantitative Trait Loci for maturity-corrected late blight resistance in tetraploid potato with PCR-based candidate gene markers[END_REF], sunflower-Phoma macdonaldii [START_REF] Darvishzadeh | Quantitative trait loci associated with isolate specific and isolate nonspecific partial resistance to Phoma macdonaldii in sunflower[END_REF], soybean-soybean cyst nematode [START_REF] Guo | Pooled analysis of data from multiple quantitative trait locus mapping populations[END_REF].

Two populations of M. truncatula (LR4 and LR5) were phonotyped to identify the genetic determinants underlying resistance in A17 and F83005.5 to C. trifolii races and E. pisi isolates. Results showed that resistance to C. trifolii is mainly by a single major locus to races, named Ct1 which is located on the upper part of chromosome 4 and resistance to E.

pisi involves three distinct loci, Epp1 on chromosome 4 and Epa1 and Epa2 on chromosome 5 (Ameline- Torregrosa et al., 2008). Jemolong A17 line is susceptible to R. solanacerum GMI1000, and disease symptoms were dependent upon functional hrp genes. A major QTL, named resistance to the necrotroph Phoma medicaginis one (rnpm1) controls mainly resistance in population of cross between A17 and SA27063. A second QTL, rnmp2 is responsible of resistance in population of cross between SA27063 and SA3054 [START_REF] Kamphuis | Two alternative recessive quantitative trait loci influence resistance to spring black stem and leaf spot in Medicago truncatula[END_REF].

Objectives of the study

1-As far as we know, the interaction between M. truncatula and other, nonhost Vaa and Vd strains is not reported in the literature. Pathogenic fungi are known for their capacity to rapidly adapt to new environments or host plants. Hence we aimed to study the potential of Verticillium strains isolated from several crops which are cultivated in Europe or isolated from soil, to cause disease in the non-host plant M. truncatula and to identify possible sources of resistance in this species. In the present research we studied the responses of 25 M. truncatula genotypes from various geographical origins to six strains of V. albo-atrum and V. dahliae under controlled conditions.

2-Based on the first part we aim to study the genetic control of resistance and susceptibility to one of the Verticillium strains which is different from Vaa V31-2, and to identify QTLs controlling the response to this strain.

3-A third objective was to describe the early effects of infection on plants. For this purpose, chlorophyll content and photosynthetic electron transport were measured in A17 and F83005.5 genotypes of M. truncatula infected with Vaa-V31-2. We hoped that the assessment of photosynthesis by means of chlorophyll fluorescence emission could be used as an early diagnostic tool for disease detection.

4-Finally, we checked if inoculations at a temperature more adapted to V. dahliae would change the susceptibility or resistance of M. truncatula to the pathogen. complete blocks design and 8-12 plants per RILs were used in each replication at three different dates.

Plants were root-trimmed by cutting approximately 1 cm from the bottom of the Jiffy pot and were inoculated by dipping the exposed roots for 30 min in the fungal spore suspension (10 6 sp/ml). The inoculated plants were then transferred to plates covered with moist soil and were kept in a growth chamber with a photoperiod of 16h and a constant temperature of 20°C.

Phenotyping

Disease symptoms

The development of symptoms was checked every 3 days during 30 days after inoculation. A disease index scale from 0 to 4 as established in our laboratory was used for the evaluation (Figure 7). Score 0 corresponds to plants without symptoms, score 1 when the first leaf was chlorotic, score 2 when the first two leaves were wilted, score 3 when the entire plant was wilted and 4 when the plant was dead. Maximum symptom scores (MSS) were determined at the end of the experiment for each plant per replication and mean values were calculated.

Area under the disease progress curve (AUDPC) was calculated according to the equation of [START_REF] Campbell | Introduction to plant disease epidemiology[END_REF] for each plant per replication, and mean values were calculated.

Fresh weight

Fresh weight (FW) was determined for the aerial part of each plant at the end of the experiment. Percentage of fresh weight (FWI/FWCX100) was calculated by dividing the mean fresh weight of inoculated plants by the mean fresh weight of control plants and multiplied by 100.

Dry weight

Dry weight (DW) of aerial parts was determined after drying them in the oven at 65°C for 72h.

Chlorophyll fluorescence

Chlorophyll fluorescence was measured for two Medicago truncatula genotypes (A17 and F83005.5) inoculated by Vaa-V31-2 or mock-inoculated at 7 days after inoculation at a temperature of 20 °C ± 3°C with a pulse-amplitude modulation portable fluorometer (Mini-PAM, Heinz Walz GmbH, Effeltrich, Germany). All measurements were carried out in the saturation pulse method described in the Mini-PAM manual. Fluorescence was measured on dark-adapted plants after having been placed in darkness for at least 30 min. Eight measurements were taken per inoculated genotype and four per control genotype. F 0 (minimal fluorescence) and Fm(maximal fluorescence) were determined upon excitation of leaves using a weak measuring light of 0.15 µmol quanta m -2 s -1 from a light emitting diode and in the form of a 800 ms pulse length at 600 Hz frequency of saturating white light. The fibre optics to sample distance and light intensity was chosen, such that the F 0 value remained under 500. The distance from fibre optics to sample was kept constant throughout the experiment. Variable to maximum fluorescence ratio was then calculated by F v /F m = (F m -F 0 )/F m [START_REF] Schreiber | Chlorophyll fluorescence as a nonintrusive indicator for rapid assessment of in vivo photosynthesis[END_REF] which represents the efficiency of open PS II. F m ̍ at steady state was measured at midday keeping ambient light at ∼200 µmol quanta m -2 s -1 . Measuring light was turned on and actinic light was applied for 30 sec. F m ̍ was determined by applying a saturation pulse of 10 000 µmol quanta m -2 s -1 . Quenching coefficients were calculated using the following equations:

. photochemical quenching, q p = (F m ̍ -F 0 ̍ )/(F m ̍ -F 0 )

. non-photochemical quenching, q N = (Fm-F m ̍ ) /(F m -F 0 )

. non-photochemical quenching, NPQ = (F m -F m ̍ )/F m ̍

. The proportion of closed PSII traps (1-q p )

Chlorophyll content

Chlorophyll content was measured for two M. truncatula genotypes (A17 and F83005.5) inoculated by Vaa-V31-2 or mock-inoculated at 8 days after inoculation. A SPAD-502 portable leaf chlorophyll meter (Minolta Corp. Ramsey, NJ) was used for non-destructive leaf chlorophyll determination on a leaf area basis. We used four plants for each control genotype and eight plants for each inoculated genotype. SPAD readings were averaged to represent one observation.

Molecular methods

DNA extraction

To extract the genomic DNA from a plant, three young leaves are harvested and placed in a well of a plate with 96 wells of 2.5 mL each. Then, 2 big glass beads and 2 small glass beads are added in each well. The leaves are dried at 65°C for 5 days, and then ground with the "glass bead grinder" (1 min at maximum power). 500 µL of extraction buffer (the composition of extraction buffer is shown in Table 5) are added to each well, the plate is shaken for 15 min and then centrifuged for 20 min at 4000 rpm. The supernatant from each well is transferred to a new plate and centrifuged 20 min at 4000 rpm; again, the supernatant is transferred to a new plate, and 300 µL of isopropanol are added to each well. The plate is shaken and centrifuged 30 min at 4000 rpm. The pellet is dried 5 min under the laminar flow hood and then re-suspended in 100 µL of DNase-free water. The plate should be kept at -

20°C.

Table 5 Composition of extraction buffer.

Extraction buffer 100 mL CTAB (Hexadecyl Trimethyl-Ammonium Bromide)

g

Tris-HCl (1 M, pH=8) 10 mL NaCl(5 M) 28 mL EDTA(0,5 M ,pH=8) 4 mL Add 0,5ml Beta-mercapto-ethanol just before extraction

Polymerase Chain Reaction (PCR)

Table 6 shows the list of the SSR markers and PCR primers that I used. The PCR mixtures for 1 µL of genomic DNA (diluted 1: 10 in sterile DNase-free water) consists of: 2,5 µL of 10X PCR Buffer (Interchim, France), 1,25 µL of MgCl 2 50 mM (Interchim, France), 1 µL of The interaction between Medicago truncatula and two soil-borne pathogens has already been characterized in our laboratory. The bacterium Ralstonia solanacearum is the causal agent of bacterial wilt, and resistance QTLs have been identified in M. truncatula, by studying a cross between the resistant parent F83005.5 and the susceptible parent A17 [START_REF] Vailleau | Characterization of the interaction between the bacterial wilt pathogen Ralstonia solanacearum and the model legume plant Medicago truncatula[END_REF]. The vascular wilt inducing fungus Fusarium oxysporum f.sp. medicaginis was also shown to infect M. truncatula, but all studied lines were susceptible (Ramirez-Suero et al., 2010), so that genetic studies on resistance to fungal soil pathogens were not possible. In order to explore defense mechanisms and genes involved in resistance to a soil-borne fungal pathogen, it was decided to set up a new pathosystem. Root inoculation assays in various conditions (in-vitro culture on solid medium, hydroponic culture, culture in peat substrate) showed that Vaa caused typical disease symptoms on M. truncatula such as chlorosis, wilting and death of plants. A scale for symptom scoring ranging from 0 to 4 was established in order to quantify disease severity (see figure 7 in Material and methods). Six M. truncatula genotypes (Jemalong A17, A20, DZA45.5, DZA315.16,F83005.5 and TN1.11) were first studied and were found to have different levels of susceptibility. A GFP-expressing V. albo-atrum strain was used to study colonisation of susceptible plants. Symptoms and colonisation pattern in infected M. truncatula plants were typical of Verticillium wilt. The fungal spores entered the xylem vessel at the cut root tips, germinated and continued to spread via the xylem vessels during the first week. At later stages when wilting symptoms were apparent, the fungus was no longer restricted to the vascular system and also colonized the cortex.

The interaction between Medicago truncatula and the

Three distinct major QTLs were identified using 3 different crosses. In recombinant inbred lines population LR3 the resistant parent was line DZA45.5 and the susceptible parent was line F83005.5. QTL mapping in this population showed one major locus on chromosome 2 and another minor locus on chromosome 6. These QTLs, called MtVa2 and MtVa3, had respective LOD scores of 6.0 and 3.6 and together accounted for 22% of the resistance phenotype. In populations LR5 and LR4 the resistant parent was line A17, and the susceptible parent lines were F83005 and DZA315.16 respectively. I participated in this work by phenotyping 173 RILs of the LR5 population in one replication. I also contributed to densify the genetic map of this cross, but the results were obtained too late to be included in the publication. One single major single QTL on linkage group 7 was identified for the two mapping populations LR4 and LR5, in three independent experiments (figure 8). This single major QTL, named MtVa1, was detected with data obtained in different sites for both populations (laboratories of Ecolab, and of the two seed companies Barenbrug and R2n). The MtVa1 QTL showed high LOD scores (up to 26 in LR5) and accounted for large effects, as it explained up to 42.5% of phenotypic variation in LR5. The occurrence of one single QTL suggests also that the two susceptible lines F83005.5 and DZA315.16 do not contain additional resistance loci with strong effects.

To check if Ve gene homologs were localised in the region underlying the QTLs, a blastp analysis on the M. truncatula genome was performed using the peptide sequence of tomato VE1 (Gene bank accession n° AAK58681.2). Eight homologous sequences were detected.

Among them, seven are localised on chromosome 4 and one on chromosome 5. Hence these homologous sequences do not co-localise with the major QTLs of partial resistance to V. albo-atrum in our pathosystem.

Symptom scoring after root-inoculation and modeling of disease curves was also used to assess the susceptibility levels in a core collection of 32 lines which represents the genetic diversity of this species in the Mediterranean region, and in mutants affected in symbiosis with rhizobia. The disease functional parameters such as symptom severity at the end of the experiment or the speed of disease onset varied largely in lines of the core collection, and were found to be independent from each other. This biodiversity with regard to disease response encourages the development of association genetics and ecological approaches.

Several mutants of the resistant line, impaired in different steps of rhizobial symbiosis, were affected in their response to V. albo-atrum, which suggests that mechanisms involved in the establishment of symbiosis or disease might have some common regulatory control points.

Improvement of the genetic map of LG7

The detected QTL for the resistance to Vaa-V31-2 is located on the chromosome 7 of M.

truncatula; this zone includes 31 BACs and two gaps. In order to improve the molecular map in the QTL confidence interval, I used 12 new markers, located on one BAC every two or three cM (all the information about the M. truncatula genome is available on the web site www.medicago.org). PCR conditions, gel electrophoresis, and genotype scoring were done as described in Materials and methods.

At first the markers Mtic 1421Mtic , 1423Mtic , 1424Mtic , 1425Mtic , 1426Mtic , 1427Mtic , 1428Mtic , 1429Mtic , 1430Mtic , 1431Mtic , 1432 and 1433 were tested with the parental lines A17 and F83005.5. PCR and electrophoresis showed a polymorphism between A17 and F83005.5 for the markers Mtic 1423Mtic , 1424Mtic , 1425Mtic , 1426Mtic , 1427Mtic , 1431Mtic and 1432;; they are also all co-dominants, except for Mtic 1427, which did not seem to amplify F83005.5. Figure 9 shows the responses of the genotyping experiment, done with these 7 markers on the 113 F8 RILs of population LR5, and analysed by PCR and electrophoresis. The A genotype indicates lines that were equal to the female parental line and the B genotype lines that were equal to the male parental line; the letter H refers to heterozygous genotype. As can be seen, all of the lines are A or B, which means that they are homozygous.

These data were integrated into the genetic map of linkage group 7, as shown in figure 10. LG7 Figure 11 Photosynthesis response of genotype A17 to infection by Vaa-V31-2, 7 days after inoculation, in plants inoculated with the fungus (inoculated) or mock-inoculated (control) and standard deviation (error bar). Taken together, the chlorophyll fluorescence parameters did not change significantly in infected plants compared to the controls, thus denoting that the electron transport of PSI1 was not affected. In our experiment Fv/Fm which shows global efficiency of PSI1 was close to 0.8 for inoculated and control plants. This indicates that the leaves were healthy which is in agreement with the absence of symptoms at 7 days after infection. [START_REF] Lorenzini | Photosynthetic response of tomato plants to vascular wilt diseases[END_REF] studied the photosynthetic response of tomato plants inoculated with Fusarium oxvsporum and Verticillium albo-atrum. His results show that photosynthetic activity and chlorophyll content of the first symptomless leaf were affected by inoculation with either Fusarium or Verticillium, after 7 days. [START_REF] Floerl | Defence reactions in the apoplastic proteome of oilseed rape (Brassica napus var. napus) attenuate Verticillium longisporum growth but not disease symptoms[END_REF] infected Brassica napus var. Napus with Verticillium longisporum VL43. Their results showed that photosynthetic CO 2 assimilation or transpiration was not affected in VL43-infected plants until 21days after inoculation. The maximum quantum yield of PSII of infected plants was then lower than that of non-infected plants (-20%), probably as the result of chlorophyll loss, which was about 17% compared with non-infected plants. [START_REF] Hampton | Impact of Verticillium wilt on net photosynthesis, respiration and photorespiration in field-grown cotton (Gossypium hersiutumL.)[END_REF] studied the impact of Verticillium wilt on photosynthesis in cotton (Gossypium hirsutum L.). Their results showed that photosynthesis of diseased lower-canopy leaves was reduced by over 65% compared to controls, and the reduction was associated with chlorophyll lose. Upper-canopy leaves of diseased plants, although showing no visible symptoms of Verticillium wilt, exhibited a 20% decrease in photosynthetic activity which was independent of changes in chlorophyll or leaf water potential. The quantum yield (PSII), the linear electron transport rate (ETR), and the lignification response (monomer composition and cross linking) were studied in three Capsicum. annuum cultivars differing in degree of tolerance. The results showed that in tolerant cultivars, both ΦPSII and ETR of inoculated plants showed significantly higher levels than controls at saturating light conditions and at early time (7 days) whereas these parameters decreased in a susceptible cultivar [START_REF] Pomar | Changes in stem lignins (monomer composition and cross linking) and peroxidase are related with the maintenance of leaf photosynthetic integrity during Verticillium wilt in Capsicum annuum[END_REF]. However, this increase was not observed under limiting light conditions. As we can see in these studies the chlorophyll fluorescence parameters and chlorophyll content of plants are affected by inoculation, but in our experiment we observed PSI1 no significant difference from control plants, Several explanations can be proposed. It is possible that the time for measuring these parameters in our experiment was too early, because the speed of symptom evolution is different in different plants and under different culture conditions. Notably light conditions could be different and could prevent an effect on photosynthesis, as reported in the study of [START_REF] Pomar | Changes in stem lignins (monomer composition and cross linking) and peroxidase are related with the maintenance of leaf photosynthetic integrity during Verticillium wilt in Capsicum annuum[END_REF]. Although it cannot be excluded that at later time points photosynthetic activity is affected by Verticillium inoculation, our results show that this parameter is not useful as a parameter for phenotyping before symptom appearance.

Genetic variability of tolerance to Verticillium albo-atrum and

Verticillium dahliae in Medicago truncatula

The interaction between Medicago truncatula and a Verticillium albo-atrum strain from the closely related crop plant alfalfa has been characterized by cytological and genetical approaches, and this study was described in the preceding chapter. However, under natural conditions many different Verticillium strains may be present in the soil, and it was interesting to study the response of M. truncatula to other strains not isolated from alfalfa. In

Genetic control of resistance to Verticillium albo-atrum strain LPP0323

Our study on genetic variability to Verticillium in M. truncatula has shown that the plant species responds differentially to various isolates of the fungus. Notably strain Vaa LPP0323 induced mild disease symptoms in line A17 which is resistant to the alfalfa isolate, whereas line F83005.5 was resistant. Since these two lines and RILs populations from their cross are well characterized, a genetic study of resistance to strain Vaa-LPP0323 was undertaken. This work is described in the chapter 3. Verticillium wilt diseases are mainly caused by two species, Verticillium albo-atrum (Vaa) and Verticillium dahliae (Vd) which differ in morphology, host range, and growth characteristics [START_REF] Schnathorst | Life cycle and epidemiology of Verticillium[END_REF]. The model legume Medicago truncatula has been established as a host plant for the alfalfa isolate Vaa V31-2 in our laboratory. Major QTLs controlling resistant towards this strain were identified, and a large biodiversity in the response to Vaa among lines from various geographical origins was revealed. In addition, it has been shown that mutant lines impaired in the nitrogen-fixing symbiosis with Sinorhizobium meliloti were also modified in their susceptibility towards Vaa V31-2 [START_REF] Ben | Natural diversity in the model legume Medicago truncatula allows identification of distinct genetic mechanisms conferring partial resistance to Verticillium wilt[END_REF]. These results confirmed that M. truncatula is a very good model to study mechanisms involved in resistance to Verticillium wilt.

In natural environments, many different strains of Verticillium are supposed to cohabitate in the soil. Since the interaction between M. truncatula and other, non-host Vaa and Vd strains has not been reported in the literature before, the main objective of this work was to identify genetic variability of M. truncatula susceptibility to Verticillium albo-atrum and Verticillium dahliae strains isolated from several crops which are cultivated in Europe or isolated from soil. We studied the responses of 25 M. truncatula genotypes from various geographical origins to six strains of V. albo-atrum and V. dahliae under controlled conditions. Analysis of variance showed that the effects of genotype and isolate, as well as of their interaction were highly significant for the two parameters Maximum Symptom Score (MSS) and Area Under Disease Progress Curve (AUDPC). The effects of genotype and strain based on MSS and AUDPC mean values showed that genotype TN8.3 was the most susceptible line and F11013-3 the most resistant, respectively. Strain Vaa V31-2 was the most aggressive and Vd JR2 the least aggressive Verticillium strain. Among the 25 M. truncatula genotypes we identified some with homogenous responses such as TN8.3 and F83005.9 that were respectively susceptible and resistant to all Verticillium strains, whereas others such as F83005.5, A17 and Salses 71B showed variable responses to the different strains. These results show high genetic variability of responses to Vaa and Vd among M. truncatula genotypes and significant statistical interaction between host plant and pathogen isolates. Large collections of populations and pure lines exist for the species M. truncatula.

The collection of INRA Montpellier contains a set of 350 natural populations collected in different countries around the Mediterranean basin (France, Spain, Portugal, Algeria, Greece, Crete) and a set of 231 introductions provided by the Australian Medicago Genetic Resources It will be interesting to perform QTL studies with additional crosses and fungal strains, in order to check if non-host resistance against different strains are based on common loci or not.

Future work to better characterise the resistance QTLs that were identified in our work should combine several approaches. First, the marker density of the genetic map could be increased by adding further markers such as microsatellites, AFLP or RAPD markers.

Another step can be increasing the number of studied recombinant inbred lines. The strength of a QTL analysis primarily depends upon the size of mapping population and the density of genetic map [START_REF] Collard | An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: The basic concepts[END_REF]. [START_REF] Darvasi | A simple method to calculate resolving power and confidence of QTL map location[END_REF] suggested increasing of RILs can increase the power of the experiment for detection of minor QTLs. They also showed that for doing exact mapping it is better to increase the number of individuals for genotyping and measure the trait only one time for each genotype instead of using a few individuals and replicate the experiment several times. The LR5 population is composed of 200 lines, but in the present study we were limited by the available number of seeds for some of them. These lines must be multiplied in the greenhouse to obtain more seeds, and then we could phenotype their response to Verticillium. Finally, RILs that were found to be heterozygous in our study will be selfed and the descendents analysed for their genotype in order to identify recombination events in the QTL region. This work will involve a very high amount of plants to be genotyped (more than 1000). Fixed homozygous recombinants can then be inoculated with Verticillium and the disease phenotype will be determined. If the number of heterozygous RILs is not high enough, we can create new heterozygous lines by crossing RILs which are of A and B genotype under the resistance QTL. These steps will help to reduce the QTL confidence interval until it contains only a small number of genes, and to detect the one (or more) gene(s) related to resistance to V. albo-atrum. The functional annotation of the genes included in the QTL zone will help in the detection of the candidate genes, by comparing them with known reistance genes or genes involved in signaling and defense. For example genes coding for receptor-like kinases are very strong candidates. Such candidate gene(s) must then be validated by functional studies which involve genetic transformation. Several approaches are possible. For example, a resistance gene can be introduced into the susceptible line and overexpressed, or its expression can be suppressed in the resistant line by silencing techniques such as RNAi or antisense strategy. Stable genetic transformation of M. truncatula is time-consuming and difficult and not possible with every genotype, but transformation of roots and phenotyping of chimeric plant is a routine technique to study the role of a gene in this plant.

From the discussed literature and from the results obtained in our laboratory, it can be seen that M. truncatula has emerged as an important model legume which has facilitated advances in the understanding of legume symbioses and opened up new areas of research into biotic stress, plant responses to pests and pathogens and plant development. The completion of sequencing data and the continued progress of bioinformatic tools are important step stones for exhaustive genetic studies. Knowledge acquired with M. truncatula can be transferred to cultivated alfalfa and other legume crops and will help to improve disease resistance and other agronomically important traits.

  Abbreviations:

  Fig. 8 59 Fig. 9 61 Fig. 10 62 Fig. 11 64 Fig. 12 64

Figure 3

 3 Figure 3 Symptoms and characteristics of plant pathogenic Verticillium spp. (A) Leaf of a tomato plant infected by V. dahliae displaying symptoms of infection. Characteristic chlorosis, wilting and necrosis symptoms are visible only on one half of the infected leaf (see circles). (B) Leaf of a tomato plant infected by V. albo-atrum showing typical Vshaped necrosis. (C) Arabiopsis thaliana 23 days post inoculation with V. dahliae showing chlorosis of rosette leaves and symptoms of early senescence. (D) Longitudinal section of the stem base of a tomato plant infected by V. albo-atrum displaying mild brown vessel discoloration (arrows). (E) Microsclerotia (arrow) produced by V. dahliae on necrotic stem tissue of tomato[START_REF] Fradin | Physiology and molecular aspects of Verticillium wilt diseases caused by V.dahliae and V.albo-atrum[END_REF].

  antimicrobial substances, are produced in large amounts only after they have been stimulated by various kinds of phytopathogenic microorganisms or by chemical and mechanical injury. Healthy cells that have been adapted to localized damaged and necrotic cells produce them in response to materials which diffuse from the damaged cells.Phytoalexins cannot be produced by damaged cells during compatible biotrophic infection.Resistant and susceptible necrotic tissues are surrounded by phytoalexins. One or more Phytoalexins reaching a concentration which is enough to limit pathogen development produce resistance. Most Phytoalexins prevent the growth of fungi which are pathogenic to plants and are toxic to these fungi. Some phytoalexins are also toxic to bacteria, nematodes, and other organisms. Plants of more than 30 families have been used to isolate more than 300 chemicals with phytoalexinlike properties from them. Plants of a family usually produce Phytoalexins with quite similar chemical structures; for example Phytoalexins of most legumes are isoflavonoides, and those of Solanaceae are terpenoids. Most Phytoalexins produced in plants are in response to infection by fungi, but it has also been shown that a few bacteria, virusesm and nematodes induce Phytoalexin production.[START_REF] Agrios | Plant pathology[END_REF].

  Legume powdery mildew caused by the biotroph Erysiphe pisi DC. has been investigated by Foster-Hartnett et al. (2007) using M. truncatula genotypes with different levels of resistance.A pathosystem between Aphanomyces euteiches, the causal agent of pea root rot disease, and the model legume Medicago truncatula was developed to gain insights into mechanisms involved in resistance to this oomycete. The F83005.5 French accession and the A17-Jemalong reference line, susceptible and partially resistant, respectively, to A. euteiches, were selected for further cytological and genetic analyses. Microscopy analyses of thin root sections revealed that a major difference between the two inoculated lines occurred in the root stele, which remained pathogen free in A17. Striking features were observed in A17 roots only, including i) frequent pericycle cell divisions, ii) lignin deposition around the pericycle, and iii) accumulation of soluble phenolic compounds. Genetic analysis of resistance was performed on an F7 population of 139 recombinant inbred lines and identified a major quantitative trait locus (QTL) near the top of chromosome 3(Pilet-Nayel., 2009; Djébali et al., 2009).

  legumes and the model legume plant Medicago truncatula. It was found M. truncatula accessions Jemalong A17 and F83005.5 are respectively susceptible and resistant to R. solanacearum GMI1000. Disease symptoms were dependent upon functional hrp genes in the bacterium. An in vitro root inoculation method was employed to demonstrate that R. solanacearum colonized M. truncatula via the xylem and intercellular spaces. R. solanacearum multiplication was restricted by a factor greater than 1 × 10 5 in the resistant line F83005.5 compared with susceptible Jemalong A17. Genetic analysis of recombinant inbred lines from a cross between Jemalong A17 and F83005.5 revealed the presence of a major quantitative trait locus for bacterial wilt resistance located on chromosome 5. The results indicate that the root pathosystem for M. truncatula will provide useful traits for molecular analyses of disease and resistance in this model plant species. The susceptibility of the model legume plant Medicago truncatula to Fusarium oxysporum was studied byRamirez-Suero et al. (

  (i) hybridization based markers such as restriction fragment length polymorphism (RFLP), (ii) PCR-based markers: random amplification of polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP) and microsatellite or simple sequence repeat (SSR), and (iii) sequence-based markers: single nucleotide polymorphism (SNP) and marker assisted selection (MAS).

Figure 6

 6 Figure 6 RILs populations (LR) obtained by crossing parental lines of Medicago truncatula. The full arrows mean that the RILs population is fixed (the lines are homozygous) and mapped; the dotted arrows mean that the RILs population is not fixed yet. This work is a collaboration of our research group with the INRA Montpellier, INRA Rennes and the center of Biotechnology of Borj Cedria (Tunisia).

Figure 7

 7 Figure 7 Symptom scale for wilt disease.

  of the interaction between Medicago truncatula and Verticillium albo-atrum: colonization pattern, QTL and biodiversity. Verticillium wilt is a major threat to alfalfa (Medicago sativa) and many other crops. The model legume and closely related species Medicago truncatula was used as a host for studying resistance and susceptibility to an alfalfa isolate of Verticillium albo-atrum. In addition to presenting well-established genetic resources, this wild plant species enables to investigate biodiversity of the response to the pathogen and putative cross-talk between disease and symbiosis. The content of this work (publication 1: Ben et al., 2013, in appendix) is briefly resumed here.

Figure 12

 12 Figure 12Photosynthesis response of genotype F83005.5 to infection by Vaa-V31-2, 7 days after inoculation, in plants inoculated with the fungus (inoculated) or mock-inoculated (control) and standard deviation (error bar).

Figure 13

 13 Figure 13Chlorophyll content in lines A17 (left) and F83005.5 (right) 8 days after inoculation by Vaa-V31-2 in plants inoculated with the fungus (inoculated) or mock-inoculated (control) and standard deviation(error bar).

  the work described below (Publication 2: Negahi et al., 2013) we surveyed genetic variability and the interaction between M. truncatula and Verticillium albo-atrum and Verticillium dahliae strains.

  3.1 below (publication 3: Negahi et al., 2013b).

Table 3 Fig. 6 49 Table 4 50 Fig. 7 51 Table 5 53 Table 6 54 Chapter 3: Results and discussion

 3

  Vd was universally accepted as a species separate from Vaa. Subsequent phylogenetic studies have clearly identified Vaa and Vd as distinct taxa

	. In
	1879, Reinke and Berthold first described wilt on potato (Solanum tuberosum), and named
	the causal agent V. albo-atrum. It was not until 1913 that a second, morphologically distinct
	species causing wilt on dahlia (Asteraceae family) was described by Klebahn, and named Vd
	(Barbara and Clewes, 2003). Verticillium spp. by convention, are identified based on the type
	of resting structures produced, namely: pigmented resting mycelium, pigmented
	microsclerotia, and chlamydospores. The two most distinctive features separating Vd and Vaa
	are: (a) the production of melanized microsclerotia as survival structures by Vd, in contrast to
	Vaa, which produces melanized hyphae but no microsclerotia (Pegg and Brady, 2002), and
	(b) although Vaa fails to grow in culture or wilt plants at 30•C, Vd grows and infects
	unhindered at 30•C. Even though this information existed in the literature, the taxonomic
	debate relative to the distinctiveness of these two species continued until the late 1970s when

  Vd strains from crucifers, as the duplication of loci prevents the generation of nit mutants

	. VCG3 and VCG6 are comprised of only
	one strain each, but VCGs 1, 2, and 4 are cosmopolitan and associated with a wide host
	range. All VCGs exhibit broad virulence, but some show differential aggressiveness. VCG4
	was subdivided into VCG4A and VCG4B; with the former more prevalent and damaging on
	potato. VCG1A was commonly associated with severe Verticillium wilt in cotton, olive, and
	woody ornamentals. Similarly, VCG2 is also subdivided into two subgroups, of which
	VCG2A is significantly more aggressive than VCG2B. Although VCGs are informative, they
	fail to describe the overall genetic diversity among strains and are seldom useful in exploring
	gene flow and the potential for sexual recombination in Vd. Moreover, VCG analysis is
	impossible in amphihaploid

Table 2

 2 The interaction of Medicago truncatula with pathogenic microorganisms

	Pathogen	Resistant line	Susceptible line QTL/ gene	Reference
	Colletotrichum trifolii	A17	F83005.5	LG4	Torregrosa et al., 2004; Yang et al., 2008
	Erysiphe pisi	A17	F83005.5	LG4 and LG5	Ameline-Torregrosa et al., 2008
	Aphanomyces euteiches	A17	F83005.5	LG3	Pilet-Nayel., 2008; Djébali et al., 2009
	Ralstonia solanacearum	F83005.5	A17	LG5	Vailleau et al., 2007
	Aphid	Jester	Jemalong	LG3	Klinger et al., 2005; Stewart et al., 2009
	Phoma medicaginis	Sa1502	Sa28645		Ellwood et al., 2006
	Fusarium oxysporum	F83005.5	A17		Ramirez-Suero et al., 2010

  Whole-genome scans for QTL detection for Verticillium resistance assessed through maximum disease index (MDI) and AUDPC parameters in LR4 and LR5 populations, for each site. Log-likelihood (LOD) score for MDI and AUDPC, as identified by Multiple QTL Mapping, are plotted against the Whole-genome of Medicago truncatula for LR4 and LR5 RIL populations. Significance of QTL is indicated by a LOD score above the threshold values, determined by a permutation analysis at the genome-wise significance level of 0.05.

	Maximum fitted disease index	AUDPC
	LR5
	Figure 8

Table 7

 7 Analysis of variance for chlorophyll fluorescence parameters of A17 and F83005.5 genotypes inoculated with Vaa-V31-2or mock-inoculated (control).

	Trait		Control	Inoculated		Effects
		A17	F83005.5	A17	F83005.5
	F0	0.662	0.787	0.509	0.666	G ns ,C ns ,GxC ns
	Fm	0.914	1.006	0.79	0.969	G ns ,C ns ,GxC ns
	Fv/Fm	0.804	0.8	0.798	0.803	G ns ,C ns ,GxC ns
	Yield	0.323	0.214	0.354	0.332	G ns ,C ns ,GxC ns
	F	0.662	0.786	0.51	0.666	G ns ,C ns ,GxC ns
	Fm'	0.914	1.006	0.792	0.97	G ns ,C ns ,GxC ns
	Qp	0.437	0.301	0.488	0.452	G ns ,C ns ,GxC ns
	Qn	0.395	0.328	0.415	0.367	G ns ,C ns ,GxC ns
	NPQ	0.522	0.389	0.583	0.485	G ns ,C ns ,GxC ns
	CH	34.95	37.205	36.007	36.586	G ns ,C ns ,GxC ns
	Fo: dark fluorescence yield ;Fm: dark maximal fluorescence yield; Fv/Fm : Maximal PSII quantum
	yield after dark adaptation; Yield ; operating quantum efficiency; F: current fluorescence yield in
	switched-on Measuring light ; Fm': maximal fluorescence yield on light ; Qp :photochemical
	quenching ;	Qn :non-photochemical	quenching ;NPQ :non-photochemical	quenching ;CH :
	chlorophyll content; G: Genotype effect ;C :condition effect ; G x C :Genotype x condition effect and
	ns :non-significant.

Acknowledgments

Chapter 2

Materials and methods

Plant material

Genotypes

M. truncatula genotypes used in this study include a core collection of 16 lines representing the genetic diversity of this species in the Mediterranean basin [START_REF] Ronfort | Microsatellite diversity and broad scale geographic structure in a model legume: building a set of nested core collection for studying naturally occurring variation in Medicago truncatula[END_REF] and lines involved in crosses for genetic studies in our department (Table 3).

A set of 118 F8 RILs (9 th generation) derived from the cross between M. truncatula parental lines A17 and F83005.5 was used in the study of genetic control of resistance. The parental lines exhibit contrasting response in their resistance to Vaa-LPP0323 strain (Figure 6).

Plant culture

The seeds, obtained from pods, are scarified with sandpaper and then placed in little Petri dishes on a piece of blotting paper imbibed with sterile water. The dishes are kept at 4°C in obscurity for 2-3 days, to overcome seed dormancy, and then for 24 h at 25°C (or for 48 h at 20°C) to let them germinate. The germinated seeds are transplanted in Jiffy pots (Jiffy, Lyon, France) as described by [START_REF] Vailleau | Characterization of the interaction between the bacterial wilt pathogen Ralstonia solanacearum and the model legume plant Medicago truncatula[END_REF] and grown in a phytotron with a photoperiod of 16h and at a temperature of 25/20°C and relative humidity of 75%.

Fungal material and culture

Six V. albo-atrum and V. dahliae strains were used for inoculations (Table 4). Vaa-V31-2 is an alfalfa strain and other strains are from tomato, potato, soil or were of unknown origin, and have not been described to infect M. truncatula before. Strain Vaa-V31-2 was obtained from Barenbrug seeds (France), strain Vaa-LPP0323 from Professor A.v. Tiedemann, University of Goettingen (Germany), and strains from Dr. B. Thomma, University of Wageningen (Netherlands). They were maintained as mycelium cultures on potato dextrose agar (PDA) medium, grown for 2 weeks at 24°C and then stored at 15°C. We tested three protocols to find the best condition for sporulation. The six Vaa and Vd strains were grown on potato dextrose agar (PDA) in Petri dishes at 24°C and spores harvested after two weeks, or after three weeks, or they were grown in PDB medium at 24°C and spores harvested after three weeks. The second protocol (growing on PDA and harvesting after three weeks) gave highest spore concentrations for all 6 strains.

Accordingly Vaa and Vd strains were grown on PDA at 24°C. Spores were harvested after 21 days of mycelial growth by flooding the Petri dishes with sterile water. The concentration of spores was determined with a Malassez counting chamber and adjusted to 10 6 spores/ml with distilled water.

Plant inoculations

The experiment was factorial with randomized complete block design and three replications.

For 25 genotype analysis with six strains eight plants per genotype were used in each replication at three different dates. For analysis RILs the experiment was randomized each dNTP 1,25 mM (Promega, Madison, WI, USA), 1 µL of each primers (Invitrogen™, France), suspended in sterile water (25 ng/µL), 0,25 µL of Taq-Polymerase and 14 µL of sterile water, for a total of 25 µL. The ordinary reaction conditions are: 94°C for 4 minutes, followed by 38 cycles of 94°C for 30 seconds, 55°C for 30 sec and 72°C for 30 sec, followed by 72°C for 6 min.

Gel electrophoresis

The amplified PCR products are separated by gel electrophoresis on 3,5% Agarose (2,6%

UltraPure Agarose + 0,9% "Low melting" Agarose) in 1XTAE buffer, and stained with ethidium bromide. The reading of the electrophoresis gel was used to design a table of the genotype of each line in the markers' zone, giving the A genotype to the lines that were equal to A17 (the female line, by convention) and B genotype to the lines that were equal to F83005.5 (the male line).

Statistical analysis

Statistical analysis for studies of pure lines (genotypes)

The effects of genotypes, strains and their interactions were identified by analysis of variance (ANOVA) with the general linear model (GLM) procedure in SAS software (SAS Institute, USA). For each analysis of variance, the normality of the residuals was tested by the Shapiro-Wilk's method. Comparison of means was done with the least significant difference (LSD) test.

Statistical analysis for studies of RILs

Analysis of variance (ANOVA) of the disease data were performed using the function 'univariate' of SPSS software (SPSS/PC-10, SPSS Inc.) It was also used to analyse the frequency distribution of RILs and their parents for partial resistance to Vaa-LPP0323 strain.

The mean of RILs and that of the parents was compared. Genetic gain was determined by comparing the mean of the 10% most resistant RILs with the mean of their parents.

QTL analysis and map construction

The linkage map used in this study is the improved map described recently by Ben et al. (2012). Briefly, the improved map has 102 new microsatellite markers. Each linkage group numbered according to the M. truncatula reference map and is presumed to correspond to one of the 8 chromosomes in the haploid M. truncatula genome (x=8). Chi square-tests were performed for segregation distortion of each locus. Loci were assembled into groups using likelihood odds (LOD) ratios, with a LOD threshold of 3.0. Multiple locus order estimates were performed for each linkage group. The likelihoods of different locus orders were compared and the locus order estimate with the highest likelihood was selected for each 57 linkage group. The Kosambi mapping function was used to calculate map distances (cM) from recombination frequencies. Mapchart 2.2 was used for graphical presentation of linkage groups and map position. QTLs for resistance to Vaa-LPP0323 isolate were detected by Multiple QTL Mapping (MQM) [START_REF] Jansen | Interval mapping of multiple quantitative trait loci[END_REF][START_REF] Jansen | High resolution of quantitative traits into multiple loci via interval mapping[END_REF] using the "qtl" package (Broman et al., 2003;Arends et al., 2010) of the R system. MSS, AUDPC and FW were used as variables for QTL detection. Additive effects of the detected QTLs, the percentage of phenotypic variation explained by each one (R 2 ) as well as the total phenotypic variation explained (TR 2 ) were estimated using the MQM programme of RQTL.

Chapter 3

Results and discussion mtic1423 B B A B A A A A B B -B A B B A A A A B A B B B A A A B A -mtic1424 B B A B A A A A B B A B A A B A

Effect of infection on photosynthesis

Several studies on the effect of pathogen infection on the plant's photosynthesis are reported, but there is little information concerning this response in Medicago truncatula -pathogen interactions. Vaa-V31-2 is one of the most aggressive soil pathogens that mainly infects M.

truncatula and can be particularly destructive for its virulence and propagation. The pathogen hits all host parts but the symptoms are not immediately visible. The objectives of the present research were to describe the early effects of infection by plants. For this purpose, chlorophyll content and photosynthetic electron transport were measured in A17 and F83005.5 genotypes of M. truncatula infected with Vaa-V31-2. We hoped that the assessment of photosynthesis by means of chlorophyll fluorescence emission could be used as an early diagnostic tool for disease detection. Thus it was studied if these traits were modified early during infection, before symptoms appeared.

The two Medicago truncatula parental lines A17 and F83005.5 were root-inoculated with Vaa-V31-2. At 7 days after the inoculation chlorophyll fluorescence of the leaves was determined, and at 8 days after inoculation leaf chlorophyll content was determined in vivo.

The experiment was factorial with randomized complete block design with five replications, eight measurements were taken per inoculated genotype and four per control genotype.Statistical analysis (ANOVA) was performed using the general linear model (GLM) procedure in the software (SAS Institute).

As shown in figure 11 7. Differences among genotypes and the genotype -condition interaction were not significant for F0, Fm, Fv/Fm, Yield, F, Fm', QP, Qn, NPQ and CH.

Effect of temperature on symptom development

V. albo-atrum and V. dahliae are found to cause disease in temperate and subtropical regions.

V. dahliae appears to be favoured by higher temperatures than V. albo-atrum, as can be deduced from its geographical distribution [START_REF] Church | Occurrence of Verticillium dahlia on sunflower (Helianthus annuus) in the UK[END_REF][START_REF] Friebertshauser | Differential-effects of the defoliating and nondefoliating pathotypes of Verticillium dahliae upon the growth and development of Gossypum hirsutum[END_REF][START_REF] Koike | Verticillium wilts of cauliflower in California[END_REF]. For our studies described above (3.1 and 3.2.1), all experiments were performed at 20°C which is the standard temperature for Vaa inoculation. The comparison between symptom curves at 24°C and 20°C (Figure 14 and 15) shows that disease symptoms develops faster and that maximum symptom scores were higher at 24°C than at 20°C, in all six lines inoculated with strain Dvd-S26. This is in agreement with the higher temperature range of V. dahliae mentioned above. Concerning strain Vaa V31-2, the resistance in line A17 was not affected by temperature, but symptoms developed slightly faster in susceptible line F83005.5 at 24°C. However, analysis of variance showed that the effects of genotype, isolate and condition were not significant for these two parameters for the two temperatures (Table 8). Since this experiment was done in only one repetition it is difficult to conclude, and we should perform two more repetitions in order to consolidate the results. b MS = mean of squares.

** ns *** no significant at 0.01 level.

Conclusion and perspectives

Center (AMGRC). This collection has been used for population studies [START_REF] Ronfort | Microsatellite diversity and broad scale geographic structure in a model legume: building a set of nested core collection for studying naturally occurring variation in Medicago truncatula[END_REF], and a set of nested core collections ranging from 8 to 96 lines has been developed. An international consortium has undertaken to re-sequence 384 lines recently in a HapMap project in order to describe genetic polymorphism and create a resource for genome-wide association mapping (http://www.medicagohapmap.org/). In our work we used the 25 lines and studied their response to Verticillium. By analyzing the responses of a larger number of genotypes to host and non-host Verticillium strains it would be possible to take advantage of the genomic tools developed for M. truncatula in order to identify genomic regions conferring resistance to Verticillium by genome-wide association studies. In addition to adding more lines to such a study, it will also be interesting to include more Verticillium isolates collected from various host plants and climate conditions. Indeed, new diseases of crop plants may develop following introduction via contaminated seeds of a same or different species or by climate change which will influence pathogen fitness or aggressiveness in the field. In order to be prepared for such potential dangers, resistance against a wide range of Verticillium isolates and under various conditions is desirable. The knowledge acquired with M. truncatula by a combination of genomics and genetic approaches should then help to develop broad durable resistance in alfalfa against this pathogen.

Another objective of this work was to identify QTLs controlling resistance to the Vaa-LPP0323 potato isolate. We found that genotype A17 was susceptible and F83005.5 was resistant. The RILs derived from the cross "A17 x F83005.5" presented highly significant genetic variation for resistance to Vaa-LPP0323 and transgressive segregation was observed.

A total of four QTLs controlling resistance to V. albo-atrum LPP0323 were detected for the parameters MSS and AUDPC. For all QTLs, those for MSS and AUDPC co-localise. The negative signs of additive effect at the different loci indicate the sole contribution of the resistant line F83005.5 for resistance to strain LPP0323. Among the QTLs identified in the present study, vwrMSS.1/ vwrAUDPC.1, located on linkage group 1, were the most important as they explain approximately 21% and 18% of phenotypic variance for resistance respectively. However, the QTLs controlling resistance against V. albo-atrum LPP0323 span regions which are too large to search for candidate genes. These large QTLs can be explained by the fact that the present study deals with resistance against a non-host strain, and those disease symptoms were not very pronounced since the susceptible parent A17 was only moderately susceptible.