C Annuum

C Frutescens

C Chinense

C Pubescens

C Chacoense

C Eximium

Baccatum Var

Pepper (Capsicum annuum L.) belongs to the Solanaceae family and it originated from South and Central America where it was domesticated around 7000 BC. The genus Capsicum includes 25 species, 5 of which are cultivated: Capsicum annuum L., C. frutescens, C. chinense, C. pubescens and C. baccatum (Eshbaugh, 1977). C. chinense originated from the Amazonian region, C. baccatum and C. pubescens had originated from Peru and Bolivia (Pickersgill, 1969), while C. annuum and C. frutescens probably originated from Mexico and central America. Pepper was introduced in Europe by Cristoforo Colombo after his first voyage to the New World (1492) and his cultivation quickly spread in the European basin. 1.1 Crop description Peppers have been domesticated for 9,000 years. The cultivation has his centre in tropical, subtropical and Mediterranean regions but it spreads all over the world in the area from southern 55° to northern 52° latitude. Of the five domesticated species, C. annuum is the most cultivated worldwide. The production of pepper for the use as spice and vegetable reached about twenty-three billion tons in 2004 (FAOSTAT 2004, F.A.O., http://faostat.fao.org) with China, Mexico and Turkey as the largest producers. The total number of cultivars at present registered to the official European Union catalogue (G.N.I.S. 2001) reached the number of 749, behind tomato, lettuce and bean for breeding activity. The chemical compositions of Capsicum fruits include vitamins from the A, B, C, E and K groups. Vitamin C (ascorbic acid) concentrations range from 0.5g to 3g per kg of fresh weight, depending on the variety, a value larger than the one of others fruits. Considerable research has focused on antioxidants in Capsicum which have reported to offer protection C.a x C.

Introduction

against cancer [START_REF] Hartwell | Plants used against cancer[END_REF]. Capsanthine and capsorubine are unique carotenoids from the pepper fruits [START_REF] Davies | The nature and biosynthesis of the carotenoids ofdifferent color varieties of Capsicum annuum[END_REF]. They are concentrated in the oleoresin and they are used as colorant by food industries.

Pungency can be considered as the most famous pepper trait. It derives from capsaicinoids, found only in the Capsicum genus, which have presumably a defence role. The amount of these substances in pepper fruits ranges from traces in sweet cultivars to a few percentage of dry weight in the Habanero fruits, the hottest pepper cultivar belonging to C. chinense.

Pepper: the plant characteristics 1.2.1 Plant morphology

Official descriptors for pepper plants and fruits are available with the aim of classifying the high variability present in the Capsicum genus and to help the characterization of pepper genetic resources. [START_REF] Ipgri | Descriptors for Capsicum, International Plant Genetic Resources Institute. Rome, Italy; the Asian Research and Development Center, Tapei, Taiwan and[END_REF].

Pepper plants have a straight primary stem with two to more than 20 internodes, resulting from the growth of its primary apex, which terminates in a flower. Two to three secondary stems develop at the top of the primary stem determining an erected habit. At each internode of the secondary stems, one flower develop in a fruit that is a berry with colors ranging from dark green to ivory-white when immature, and from ivory-yellow to red when mature. Fruit shape ranges from round to ovate or highly elongated with a fruit weight comprised from less than one gram in wild plants to 500 grams for the most productive cultivars (Figure 1). Mature seeds are attached to placenta veins ant their amount is about 120-150 seeds per gram.

Reproductive System

Pepper is considered an autogamous plant. However flowers produce a lot of nectar as resulting in a partially allogamous reproductive behaviour, depending on the activity of pollinator insects and the climate.

Thus Capsicum can be considered facultative cross -pollinating species [START_REF] Odland | A study of natural crossing in peppers (Capsicum frutescens)[END_REF][START_REF] Franceschetti | Natural cross pollination in pepper (Capsicum annuum L.). Eucarpia Meetingon Genetic and Breeding of Capsicum[END_REF][START_REF] Tanksley | Linkage relationships and chromosomal locations of enzyme-coding genes in pepper, Capsicum annuum[END_REF]. The amount of cross-pollination is a key element in breeding and production.

For example in protected cropping system, honeybees are used for the pollination to obtain well shaped fruits with more seeds.

Agroclimatic requirements

Several sources of information concerning pepper cultural practices are available (De Witt and Bosland 1993[START_REF] Nuez | El Cultivo de Pimentos, Chile y Ajies[END_REF][START_REF] Siviero | La coltivazione del peperone[END_REF][START_REF] Erard | Le poivron. Ed. Centre Technique des Fruits et Légumes[END_REF]. Optimum seeds germination temperature is at 25-30°C, while the best growing and fruit development temperature is comprised between 21 and 29°C. [START_REF] Nonnecke | Vegetable production[END_REF]. Temperatures exceeding 32°C or lower than 15°C lead to a retarding in growth, blossoms falling and yield decreasing [START_REF] Knott | Eggplant, tomato and pepper[END_REF].

However, flowering and fruit-set return to normality as temperatures return to the optimum (Greenleaf 1986). On the contrary, C. chinense which originated from the Amazonian lowlands, is well adapted to very hot and humid climates. An excess or deficit of water during flowering and fruit set induces flower abortion or further blossom end rot of the fruits. Finally peppers are considered photoperiod-insensitive [START_REF] Knott | Eggplant, tomato and pepper[END_REF].

Diseases and pest

Pepper is attacked by several pathogens, including viruses, fungi, oomycetes bacteria and nematodes. Intensive cultivations together with climatic conditions in some cultivation regions favour the development of epidemics.

Viral diseases

More than twenty viruses are responsible of attacks on pepper. Viruses which are transmitted in mechanical way (as tobamoviruses) are more frequent in protected crops, while viruses transmitted by insects are prevalent in open fields. Cucumber mosaic virus (CMV) is one of the most important virus diseases of pepper worldwide. CMV is spread by many aphid species in a nonpersistent manner, meaning that insecticides cannot prevent the spread of this disease. Several strains of the virus exist, and all are able to infect pepper with a peculiar symptom expression. The age of a plant at the time of infection strongly influences the severity of epidemics and production losses as well as the type of symptoms (Figure 2). No major genes for CMV resistance have been identified, but several sources of partial resistance have been identified (Pochard and Daubeze 1989[START_REF] Dufour | The distribution of cucumber mosaic virus in resistant and susceptible plants of pepper[END_REF][START_REF] Nono-Womdim | Study of multiplication of cucumber mosaic virus in susceptible and resistant Capsicum annuum lines[END_REF], Ben Chaim et al. 2001b, Caranta et al. 1997b, Caranta et al. 2002) which conferred a good level of resistance in the field. Depending on the virus strain-plant genotype interaction, susceptibility results in vein mosaic or necrotic symptoms in leaves and fruits (Figure 4). Tobacco etch virus (TEV), Pepper mottle virus (PepMoV), Pepper severe mosaic virus (PSMV) and Pepper yellow mosaic virus (PYMV) are common in North and South-Central America. Major recessive or dominant resistance genes have been characterized [START_REF] Kyle | Proposed revision of nomenclature for potyvirus resistance genes in Capsicum[END_REF]) and introduced into most modern pepper cultivars. Polygenic and quantitative resistance has also been identified in many local populations from different origins [START_REF] Kuhn | Multiple levels of resistance to tobacco etch virusin pepper[END_REF][START_REF] Caranta | Both common and specific genetic factors are involved in polygenic resistance of pepper to several potyviruses[END_REF], Caranta et al. 1997a). Tomato spotted wilt virus (TSWV) can cause disease in a wide variety of plants including pepper, tomato, and lettuce. The virus is common in both temperate and subtropical areas of the world. The virus is transmitted by thrips in a persistent manner with acquisition of the virus by the larvae and transmission after a 4 to 10-day latent period.

Symptoms are highly variable, depending on the plant genotype, plant stage and agroclimatic conditions (Figure 5). In pepper a single dominant gene Tsw confers resistance to TSWV and it has been introduced from C. chinense into C. annuum [START_REF] Black | Tomato spotted wilt virus resistance in Capsicum chinense PI152225 and 159236[END_REF], Moury et al. 1997). Several commercial hybrids containing the Tsw resistance genes have been commercialised, but new TSWV strains breaking down this resistance gene are known in different production regions.

Fungi and Oomycetes

Pepper is susceptible to soilborne fungi and Oomycetes both in field and in protected cropping systems. The Oomycete Phytophthora capsici is the major cause of pepper root rot worldwide, causing necrotic lesions on lower stems, branches, leaves and fruits leading to the wilt of the plants and their death (Figure 6). Other important soilborne fungi causing plant wilt are Verticillium dahliae, Phytophthora parasitica, Fusarium oxysporum and Rhizoctonia solani which form a complex in most soils where peppers are repeatedly cultivated. Verticillium dahliae is widespread in temperate climate and it causes plant wilt with an initial dryness of the margin of older leaves. Principal cultural practices that reduce soilborne diseases include drip irrigation and well-drained soils. Soil treatments with chemicals (in particular with the methyl bromide) were applied in greenhouses and allow the reduction of the disease incidence but their utilisation is progressively banned due to their environmental impact. Several sources of partial and polygenic resistance against P. capsici and V. dahliae were characterized in many local hot pepper cultivars and were introduced in a few large fruited cultivars (Palloix et al. 1990 a and b, [START_REF] Poulos | Pepper breeding (Capsicum spp.): achievements, challenged and possibilities[END_REF][START_REF] Thabuis | Phenotypic and molecular evaluation of a recurrent selection program for a polygenic resistance to Phytophthora capsici in pepper[END_REF] a and b) but the complex genetic structure of the resistance [START_REF] Lefebvre | Molecular Markers for Genetics and Breeding: Development and Use in Pepper (Capsicum spp.)[END_REF]Palloix 1996, Thabuis et al. 2003) makes it difficult to combine a high level of resistance with good agronomic performances Principal airborne fungi attacking pepper are powdery mildew (Leveillula taurica) which causes plant defoliation, Cercospora capsici causing foliar necrotic ringspots and plant defoliation, and anthracnose caused by Colletotrichum spp which produces mature fruit rot (Figure 7). Several fungicides may be used against those pathogens however; their efficiency is reduced since the primary infection occurs several weeks before symptoms appearance. Genetic sources of resistance were characterized against powdery mildew, Cercospora capsici and anthracnose in local hot pepper landraces of C. annuum and C. chinense [START_REF] Daubèze | Resistance to Leveillula taurica in pepper (Capsicum annuum) is oligogeniccally controlled and stable in Mediterranean regions[END_REF], Lefebvre et al. 2003[START_REF] Lim | Optimal conditions for resistance screening of Cercospora leaf spot by Cercospora capsici on pepper[END_REF][START_REF] Pakdeevaraporn | QTL mapping of Anthracnose (Colletotrichum capsici) in Chilli[END_REF], Voorrips et al 2004).

Bacterial diseases

The two main bacterial diseases affecting pepper are bacterial leaf spot, caused by Xanthomonas campestris pv. vesicatoria and bacterial wilt, caused by Ralstonia solanacearum.

X. campestris causes necrotic or water-soaked lesions on pepper leaves, fruits and stems. It can survive on leaf surface of many weeds and plant debris (Figure 8) and it is transmitted by contact, rain splashes and seeds. Principal agricultural practices include crop rotation and seed disinfection. Chemicals (in particular copper spray) are useful in pest management but resistant strains were found (Ritchie and Dittapongpitch 1991). Several major genes (Bs1, Bs2, Bs3) were introgressed in pepper cultivars but it was found that they confer a partial 13 resistance, depending on the prevalent races of the bacteria. A high ability to generate multi-virulent races is noted [START_REF] Hibberd | Different phenotypes associated with incompatible races and resistance genes in bacterial leaf spot in pepper that is simply inherited[END_REF][START_REF] Minsavage | Gene-for-gene relationships specifying disease resistance in Xanthomonas campestris pv. vesicatoria-Pepper interactions[END_REF][START_REF] Kousik | Response of bell pepper cultivars to bacterial spot pathogen races which individually overcome major resistance genes[END_REF]. Alternative sources of resistance were also identified that do not display race [START_REF] Poulos | Heritability and gain from selection for quantitative resistance to Xanthomonas campestris pv. vesicatoria in Capsicum annuum L[END_REF][START_REF] Szarka | General defence system in the plant kingdom[END_REF].

Figure 8: leaf necrosis and spots on fruits due to Xanthomonas vesicatoria;

(INRA) R. solanacearum is a soilborne bacterium that infects plant roots, spreads in the plant stems and causes plant wilt at any development stage (Figure 9). R. solanacearum also infects many other hosts including solanaceous crops. Very few preventive measures are efficient, except complex organic soil amendments (Hayward 1991, Fegan and[START_REF] Fegan | How complex is the "Ralstonia solanacearum species complex[END_REF]. Partial resistance with oligogenic control to this pathogen was identified in pepper germplasm collections and it is at present available only in local cultivars [START_REF] Singh | Screening of sweet pepper germplasm for resistance to bacterial wilt (Ralstonia solanacearum)[END_REF], Kim and Kim 2004[START_REF] Lafortune | Partial resistance of pepper to bacterial wilt is under oligogenically controlled and efficient under hot and rainy season in tropical climate[END_REF].

Nematodes

Root-knot nematodes "RKN" (Meloidogyne spp.) are pathogenic on several solanaceous crops, especially peppers, potatoes, and tomatoes [START_REF] Khan | Comparative damage potential and reproduction efficiency of Meloidogyne javanica and races of M. incognita on tomato and eggplant[END_REF]Haider 1991, Sasser 1977) and are responsible of stunting, wilting or chlorosis (yellowing) with a reduction in plant yield. They are harmful pests particularly under hot climates and under plastic tunnels and greenhouses, where their multiplication occurs continuously [START_REF] Babaleye | Nematodes, an increasing problem in tropical agriculture[END_REF]. Four species of RKN, Meloidogyne incognita (Kofoid & White) Chitwood, M. hapla Chitwood, M. javanica (Treub) Chitwood, M. arenaria (Neal) Chitwood cause severe attacks, particularly in the Mediterranean area and in central Africa and America [START_REF] Fery | Southern root-knot nematode of pepper, Studies on value of resistance[END_REF][START_REF] Lindsey | Influence of initial population densities of Meloidogyne incognita on three chilli cultivars[END_REF], Thies et al. 1997). The most common preventive measure was the methyl bromide, but it has been prohibited in industrialized countries since 2005, and will be prohibited in developing countries in 2015 (Federal Register of U.S. Environmental Protection Agency, 2004). New alternatives to methyl bromide have been proposed, as soil solarization which are limited to protected cropping systems and climatic conditions that permit this technique, i.e. soil temperature of 50-55°C for at least thirty days. Soil solarization and crop rotation can be combined with chemicals like metham sodium, 1-3-dichloropropene, or dazomet. The development of new resistant cultivars can be considered as the main alternative to the utilisation of chemicals, particularly in pepper where a wide range of resistance genes with a large spectrum of action were characterized and identified.

These included the N dominant gene (efficient only against some Meloidogyne species when transferred into susceptible cultivars), the resistance founded by Di [START_REF] Vito | Resistance of Capsicum species to Meloidogyne incognita[END_REF] and [START_REF] Vito | Genetic of resistance to root-knot nematodes (Meloidogyne spp.) in Capsicum chacoense, C. chinense and C. frutescens[END_REF] in some lines of C. chacoense, C. chinense, and C. frutescens . in addition several dominant genes (Me genes) in C. annuum [START_REF] Djian-Caporalino | Highresolution genetic mapping of the pepper (Capsicum annuum L.) resistance loci Me3 and Me4 conferring heat-stable resistance to root-knot nematodes (Meloidogyne spp.)[END_REF] were also identified, which display large spectrum and heat stable resistance with different resistance expression ranging from initial limitation of nematode penetration, post-penetration biochemical responses or hypersensitive response [START_REF] Djian-Caporalino | Spectrum of resistance to root-knot nematodes and inheritance of heat-stable resistance in pepper (Capsicum annuum L.)[END_REF][START_REF] Pegard | Histological Characterization of Resistance to Different Root-knot Nematode species related to phenolics accumulation in Capsicum annuum L[END_REF].

Cytogenetics

Pepper basic chromosome number is 12, as many other important Solanaceae species (tomato, potato, eggplant). The physical size of the genome (from 2200 to 2700 Mbp) averages three to four times that of tomato (750 Mbp) or diploid potato (1000 Mbp) [START_REF] Arumuganathan | Nuclear DNA content of some important plant species[END_REF]. All the Capsicum species present a very homogeneous caryotype with 1 to 2 pairs of acrocentric chromosomes and 11 pairs of meta-or submetacentric chromosomes (Figure10).

The analysis of the inter-specific hybrids considering the five domesticated species indicate exchanges of chromosome ends for seven of the 12. The number and position of translocations correlates with distances between taxa and fertility of hybrids (Gonzalez de Leon 1986[START_REF] Pickersgill | Cytogenetics and evolution of Capsicum L[END_REF]. Isozyme markers were linked with chromosomal interchanges among C. annuum, C. chinense and C. baccatum [START_REF] Tanksley | Linkage relationships and chromosomal locations of enzyme-coding genes in pepper, Capsicum annuum[END_REF], Gonzales de Leon 1986) while localization of chromosome breakpoints in present maps remain to be established.

Information at present available shows that C. annuum and C. chinense differ by one or two translocations plus one chromosome satellite, affecting chromosome segregation [START_REF] Lanteri | Lack of a caryotype class and skewed chromosome segregation in two backcross progenies of Capsicum[END_REF]. That may explain the discrepancies between the chromosomes P1 and P8 in the inter-specific map of [START_REF] Livingstone | Genome mapping in capsicum and the evolution of genome structure in the Solanaceae[END_REF] and the C. annuum intra-specific maps of [START_REF] Lefebvre | Construction of an intraspecific integrated linkage map of pepper using molecular markers and doubled haploid progenies[END_REF][START_REF] Lefebvre | Towards the saturation of the pepper linkage map by alignment of three intraspecific maps including known-function genes[END_REF]. 1.4.1 Pepper genetic linkage map. [START_REF] Pochard | Description des trisomiques de piment (Capsicum annuum L.) obtenus dans la descendance d'une plante haploïde[END_REF] selected a complete set of the 12 primary trisomics in the self haploid progeny of C. annuum. These 12 were named by using French coding names representing a colour (violet, indigo, bleu, violet, vert, jaune, orange, rouge, pourpre, noir, brun and bistre). Later, 10 monogenic traits and few isozyme markers were mapped in seven of the 12 trisomics [START_REF] Pochard | Localization of genes in Capsicum annuum L. by trisomic analysis[END_REF][START_REF] Pochard | Localization of vy2 and fa genes by trisomic analysis[END_REF][START_REF] Tanksley | Linkage relationships and chromosomal locations of enzyme-coding genes in pepper, Capsicum annuum[END_REF]. The development of DNA -based markers, in particular with those based on the hybridization analysis of restriction fragment length polymorphism (RFLP) and those based on the polymerase chain reaction (PCR) technique (AFLP, SSR, RAPD SSAP and SNP), allowed the detection of more polymorphism markers than isozyme. [START_REF] Tanksley | Conservation of gene repertoire but not gene order in pepper and tomato[END_REF] and [START_REF] Prince | Construction of a molecular linkage map of pepper and a comparison of synteny with tomato[END_REF] constructed the first genetic linkage maps of pepper using RFLP markers. Subsequently, both intra-specific and inte-rspecific crosses were used to generate linkage maps (Table 1). Inter-specific maps were generally preferred thanks to their higher level of polymorphism detected (generally up to 80%) which allow the genetic map to be more saturated. Parents used for inte-rspecific crosses include C. annum and C. chinense [START_REF] Livingstone | Genome mapping in capsicum and the evolution of genome structure in the Solanaceae[END_REF][START_REF] Kang | An interspecific (Capsicum annuum × C. chinense) F2 linkage map in pepper using RFLP and AFLP markers[END_REF], but also C. annuum and C. frutescens (Rao et al. 2003 andSasvari et al. 2004). C. annuum x C. chinense are generally preferred due to their better compatibility and fertility level. Intra-specific maps were later constructed by [START_REF] Lefebvre | Construction of an intraspecific integrated linkage map of pepper using molecular markers and doubled haploid progenies[END_REF][START_REF] Lefebvre | Towards the saturation of the pepper linkage map by alignment of three intraspecific maps including known-function genes[END_REF], Ben Chaim et al. (2001a), [START_REF] Ogundiwin | Construction of 2 intraspecific linkage maps and identification of resistance QTLs for Phytophthora capsici root-rot and foliar-blight diseases of pepper (Capsicum annuum L.)[END_REF], and [START_REF] Sugita | Rapid construction of a linkage map using High-efficiency Genome Scanning/AFLP and RAPD , Based on an Intra-specific, Doubledhaploid Population of Capsicum annuum[END_REF] which also include maps coming from a cross between a commercial variety and an exotic accession characterized by a high level of resistance to several pathogens. Although inter-specific progenies allow more polymorphisms to be detected than intra-specific progenies, they suffer from segregation distortion, low fertility, and major structural rearrangements [START_REF] Lanteri | Lack of a caryotype class and skewed chromosome segregation in two backcross progenies of Capsicum[END_REF][START_REF] Lanteri | Chromosomal structural changes in Capsicum annuum L. and Capsicum chinense[END_REF], which limit the power of the linkage analysis and restrict their relevance to markerassisted selection applications. On the contrary, intra-specific maps are more reliable as they show high fertility level, high recombination rates and undistorted segregation [START_REF] Lefebvre | Towards the saturation of the pepper linkage map by alignment of three intraspecific maps including known-function genes[END_REF].

The main limiting aspects in pepper maps are their unsaturated condition and their reduced genome coverage, even if more linkage groups than chromosomes are reported. Thanks to the use of anchor markers (in particular RFLP), the LGs assignment to chromosomes was achieved (Lefevbre et al. 2002), which also allowed the establishment of AFLP homologies among pepper crosses [START_REF] Lefebvre | Towards the saturation of the pepper linkage map by alignment of three intraspecific maps including known-function genes[END_REF][START_REF] Paran | An integrated genetic linkage map in pepper (Capsicum spp.)[END_REF]).

An integrated map, based on six populations from inter-specific and intra-specific crosses and consisting of 2262 markers covering 1832 cM, has recently been assembled [START_REF] Paran | An integrated genetic linkage map in pepper (Capsicum spp.)[END_REF]). This integrated map improved the markers density reaching an average map distance lower than 1 cM (0.8 cM), and also the genome coverage. However, confidence in marker position and order remains low, particularly with regard to population-specific markers which appeared to grouped in terminal parts of chromosome arms. These clusters of population specific markers mainly result from the lack of markers shared between the populations, impeding a stringent integration of the marker position.

It also results from chromosomal translocations between genomes from different species. [START_REF] Pickersgill | Cytogenetics and evolution of Capsicum L[END_REF] been based on a rather low number of individuals per progeny (commonly between 40 and 100, rarely up to 200), resulting in a poor level of resolution [START_REF] Lefebvre | Molecular Markers for Genetics and Breeding: Development and Use in Pepper (Capsicum spp.)[END_REF]). As the resolution of a genetic map depends on the number of recombination events in the population, improvement can be achieved by increasing the number of individuals and generations in parallel to the number of markers used to identify recombination events. Mapping in a single large population generates a more reliable and accurate map than an integrated map derived from independent mapping populations.

1.4.2 Synteny among pepper and other Solanaceae.

RFLP markers are applicable to several different species allowing the comparison and the alignment of different genomes. Synteny (the preserved linkage of genes between related species) has as purpose to understand species evolution together with genes and noncoding regions function. It also provides a practical interest since basic knowledge from model species can be transferred to syntenic genomes to help locus or gene location. In the Solanaceae family, synteny has been studied using RFLP markers on the four most important species:

i.e. pepper, tomato, potato and eggplant. The tomato and pepper chromosomes 2, 4, 6 and 10 are conserved even if some paracentric inversions are present. For the rest of the genome, it seems that only chromosome arms remain conserved together with nonreciprocal or pericentric and paracentric inversions. On the whole, it seems that chromosome breakages occurred at centromeres and certain pepper chromosomes seem to result from more rearrangements of the tomato chromosomes [START_REF] Tanksley | Conservation of gene repertoire but not gene order in pepper and tomato[END_REF][START_REF] Livingstone | Genome mapping in capsicum and the evolution of genome structure in the Solanaceae[END_REF], Lefebvre et al. 2002) (Figure11). Tanskley et al. (1988) reported that a minimum of 32 breakages of tomato chromosomes must be generated to account for the position of orthologous genes in pepper. This value is certainly underestimated but it is the result of the divergence between the two species.

Mapping traits of interesting

The genetic linkage maps constructed in the last 10 years are powerful tools for mapping major genes and QTLs for both resistance and horticultural traits. Many Mendelian genes and quantitative trait loci controlling qualitative and quantitative resistances to various pests and pathogens have been mapped, as the resistance to Phytophthora capsici, the fungus Leveillula taurica, and the Cucumber mosaic virus (CMV). In addition, genes for resistance to diverse Potyviruses (PVY, TEV, PVMV, and PepMoV), the Tomato spotted wilt virus (TSWV), the root nematodes of the genus Meloigogyne, the tobacco mosaic virus (TMV) and to the bacterium Xanthomonas campestris, have been identified. Moreover several horticultural traits of primary importance for fertility and fruit characteristics were recently mapped (Figure 12).

Monogenic and polygenic traits

Several markers are at present available for both horticultural and resistance monogenic traits (Tab.2). The gene cl (chlorophyll retainer) mapped on chromosome P1 have been found to be collinear to the one mapped on tomato chromosome P8 [START_REF] Efrati | Molecular mapping of the chlorophyll retainer (cl) mutation in pepper (Capsicum spp.) and screening for candidate genes using tomato ESTs homologous to structural genes of the chlorophyll catabolism pathway[END_REF]) and it could be syntenic to the chromosome P8 in intra-specific maps. Marker linked to C gene was also mapped [START_REF] Lefebvre | Construction of an intraspecific integrated linkage map of pepper using molecular markers and doubled haploid progenies[END_REF], Lefebvre et al. 2002[START_REF] Blum | Molecular mapping of the C locus for presence of pungency in Capsicum[END_REF], Lee et al. 2005[START_REF] Sneath | The Pun1 gene for pungency in pepper encodes a putative acyltransferase[END_REF] and it was mapped on chromosome P2. Moreover markers linked to the Me3 and Me4

genes conferring resistance to nematodes were mapped on chromosome P9 [START_REF] Djian-Caporalino | Highresolution genetic mapping of the pepper (Capsicum annuum L.) resistance loci Me3 and Me4 conferring heat-stable resistance to root-knot nematodes (Meloidogyne spp.)[END_REF], 2006). With the advent of SSR and SNP markers, new and more reliable markers are today available for the precise identification of monogenic genes of interest, allowing a more precise localization for marker assisted-selection activities. is at a syntenic position with the resistance QTL on tomato chromosome T4 and potato chromosome IV Lefebvre 2004). The two resistance QTLs to powdery mildew due to L. taurica mapped on pepper chromosomes P6 and P9 collinear to R genes and QTLs controlling the resistance response to powdery mildew on the tomato chromosomes T6 and T12 [START_REF] Lefebvre | QTLs for resistance to powdery mildew in pepper under natural and artificial infections[END_REF]. The tomato pot-1 gene conferring resistance to PVY and TEV is collinear with the pepper pvr2 locus [START_REF] Parrella | Recessive resistance genes against potyviruses are localized in collinear genomic regions of the tomato (Lycopersicon spp.) and pepper (Capsicum spp.) genomes[END_REF] and it was demonstrated to be the same coding gene (Ruffel 2004[START_REF] Ruffel | The recessive potyvirus resistance gene pot-1 is the tomato orthologue of the pepper pvr2-eIF4E gene[END_REF].

Carrierchromosome

Locus

Horticultural traits are more and more investigated (Tab.3). Different genes controlling Mendelian traits, like pungency, fruit colour, fruit texture have been mapped using the candidate gene approach. QTLs controlling horticultural traits were reported by several authors. Ben Chaim et al. (2001a), using an intra-specific C. annuum cross, analysed a total of 14 horticultural traits, including fruit weight, fruit shape, pedicel diameter but also degree of green and red colour. Ben Chaim et al. 2003). Furthermore, several pepper fruit -related QTLs were located in genome regions which correspond to the same traits in tomato (Figure 12). Ben Chaim et al. (2001a) in pepper could be orthologous in tomato [START_REF] Lippman | Dissecting the genetic pathway to extreme fruit size in tomato using a cross between the smallfruited wild species L. pimpinellifolium and L. esculentum, var. Giant Heirloom[END_REF].

(
In addition, one pericarp width QTL (perwd1.1) could correspond to a tomato pericarp thickness QTL (Fulton et al. 2000). Finally, the tomato plant height QTL ht3 (deVicente and Tanksley 1993) could correspond to the pepper QTL ph3.1.

Comparisons of QTL position for fruit weight, shape and colour in eggplant with tomato, potato and pepper revealed a partial synteny among Solanaceae [START_REF] Djian-Caporalino | Root-knot nematode (Meloidogyne spp.) resistance genes Me in pepper (Capsicum annuum L.) are clustered on the P9 chromosome Submitted[END_REF]. For example the QTL fw2.1 detected in eggplant [START_REF] Djian-Caporalino | Root-knot nematode (Meloidogyne spp.) resistance genes Me in pepper (Capsicum annuum L.) are clustered on the P9 chromosome Submitted[END_REF] seems is colinear to both the major effect fruit weight QTL fw2.2 in tomato (Frary et al.2000) and the QTL fw2.1in pepper (Ben Chaim et al. 2001a). The eggplant QTL ovs4.1 controlling the fruit shape seems to correspond to fs10.1 in tomato (Grandillo et al. 1999) andpepper (Ben Chaim et al. 2001a).

Others important orthologies have been detected, but they are limited to eggplant, potato and tomato, such as the major anthocyanin QTL in eggplant which seems to correspond to orthologous regions in tomato and potato. In pepper no information are available for many traits already mapped in others species, in particular in tomato, thus a target for future research seems to be the analysis of others traits, with the aim of allowing the comparison of QTLs location in the most important Solanaceae species to better understand the genome organization.

Pepper breeding targets

The main breeding objectives in pepper is similar to those for other crop plants and includes the adaptation to abiotic stresses, the improvement in fruit quality and yield, and the resistance to pests and diseases.

Adaptation to abiotic stresses

The main abiotic stresses affecting pepper are hydric (including flooding, drought and salinity), energetic (including low light intensity), and supraor suboptimal temperatures which are responsible in yield and quality losses. Abiotic stresses influence traits which are generally quantitative and polygenic and their interactions have to be taken into account, leading to a hard task for breeders.

Horticultural aspects and fruit quality

Breeding for horticultural traits is performed considering standard criteria for every specific cultivar type: i.e. fruit width and length, fruit shape, number of locules and pericarp thickness. These traits are highly

Disease and Pests

Efforts in breeding for resistance to pests and diseases previously described, firstly tried to introgress resistance components in cultivated Phytophthora root rot, partially resistant cultivars were also delivered that were successful in North-Mediterranean and temperate cultivation regions. However, the resistance level was proved to be weak in central America, Asia and middle East where the pathogen strains proved to be more aggressive. One of the main target for pepper breeders is now to increase the level of resistance by combining resistance components from non-commercial varieties into productive cultivars.

BREEDING METHODS

Pepper is an autogamous genus and breeders always considered it an inbred. Selection for new cultivars was performed by using massal selection until the 1950's. First breeding activities on scientific basis started by introgressing monogenic resistances to viruses (Greenleaf 1956[START_REF] Cook | Multiple virus disease resistance in a strain of Capsicum annuum[END_REF][START_REF] Cook | Genetics of resistance in Capsicum annuum to two virus diseases[END_REF] (1980), and[START_REF] Dumas De Vaulx | Culture in vitro d'anthères de piment (Capsicum annuum L.) : amélioration des taux d'obtention de plantes chez différents génotypes par des traitements à 35°C[END_REF] and was further improved by several authors [START_REF] Mityko | Anther-culture response in different genotypes and F1 hybrids of pepper (Capsicum annuum L.)[END_REF] with the aim of increasing the rate of haploid regeneration. Up to now, double haploids are used to create new genitors from heterozygous plants which are interesting for certain traits in early stages of pedigree selection [START_REF] Pochard | The use of androgenetic autodiploid lines for the analysis of complex resistance systems in the pepper[END_REF]) and to evaluate genetic gain during selection [START_REF] Thabuis | Phenotypic and molecular evaluation of a recurrent selection program for a polygenic resistance to Phytophthora capsici in pepper[END_REF].

Backcrossing programs remain probably the most frequently breeding technique used for introducing major genes of interest coming from exotic accessions into cultivars. The main limit remains the time needed to recover the genomic background of the receiving parent in which genes have been introgressed. Backcrosses also proved ineffective to breed for polygenic resistance due to the progressive loss of favourable alleles. The phenotypic and molecular evaluation of a breeding program was performed by Thabuis et al (2004a), showing that direct backcrossing lead to a decrease of resistance to P. capsici associated with the loss of resistance QTLs, whereas intercrossing between resistant populations allowed to increase the number and frequency of favourable alleles. Thus, recurrent selection of multiallelic populations was largely used in pepper for resistance to bacteria [START_REF] Poulos | Heritability and gain from selection for quantitative resistance to Xanthomonas campestris pv. vesicatoria in Capsicum annuum L[END_REF], soilborne Fungi and oomycetes (Palloix et al 1990a(Palloix et al , 1990b) ) and viruses [START_REF] Palloix | Construction of diseaseresistance systems fitting cultivation conditions in pepper[END_REF][START_REF] Ahmed | Constructing multiresistant genotypes of sweet pepper for cultivation in the tropics[END_REF]. In these breeding programs, alleles from different genetic origins were progressively associated in elite genotypes, delivering transgressive phenotypes ie. homozygous individuals with higher resistance level than the original parental lines.

Marker assisted selection

Marker-assisted selection (MAS) is often considered as the new key technique in breeding program, permitting to increase efficiency in plant breeding compared to phenotypic selection. Thanks to high resolution mapping, markers tightly linked to QTLs of interest for horticultural and resistance traits can indeed improve the selection of favourable alleles at targeted loci. The performance also depends on the capacity to generate specific markers as tools to identify plants carrying genes and QTLs of interest.

The MAS technique has several advantages:

i)

The direct selection of the expected allele combination at the QTLs (foreground selection) instead of resulting phenotype.

ii)

The reduction of environmental effects on phenotypic evaluation which allows the heritability of the traits to be increase.

iii)

The selection of useful genotypes at early stages of development.

iv)

The possibility of genetic background selection, accelerating the return to the expected genotype and phenotype when introgressing a new trait (background selection) [START_REF] Thabuis | Construction de résistance polygénique assistée par marqueurs : application à la résistance quantitative du piment[END_REF][START_REF] Thabuis | Phenotypic and molecular evaluation of a recurrent selection program for a polygenic resistance to Phytophthora capsici in pepper[END_REF][START_REF] Collard | An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: The basic concepts[END_REF] v)

The ability of avoiding the transfer of undesirable or deleterious genes ('linkage drag'; in particular when introgressed genes come from wild species) [START_REF] Collard | An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: The basic concepts[END_REF].

Limits to MAS generally referred to:

i) The reduce number of loci which can be introgressed. From previous studies [START_REF] Hospital | Marker-assisted introgression of quantitative trait loci[END_REF] the simultaneous introgression of more than 4 QTLs requires large populations or a precise knowledge on the position of QTLs of interest.

ii) The precision of the genetic linkage map used for QTL analysis. A key aspect for the MAS is the availability of markers flanking QTLs of interest at less than 20 cM (confidence interval). More markers are needed when the confidence interval is > 20 cM. This leads to the necessity of developing high resolution genetic linkage maps with the aim of increasing precision in QTL localisation. These maps are based on large number of individuals, which allow to exploit more meiosis, thus increasing the precision in mapping. The number of individuals is also the parameter which more influences the QTL analysis [START_REF] Moreau | Markerassisted selection efficiency in populations of finite size[END_REF]): more individuals used for phenotypic tests permit to better dissect the genetic variability of complex traits, thus increasing the precision of QTL detection.

iii) The cost for MAS compared to conventional plant breeding depends by several parameters, i.e. genotyping for map construction (in particular for developing molecular markers), inheritance of the trait, method of phenotypic evaluation, field/glasshouse and labour costs, and the cost of resources. [START_REF] Dreher | Money matters (I): costs of field and laboratory procedures associated with conventional and marker-assisted maize breeding at CIMMYT[END_REF] indicated that the cost-effectiveness needs to be considered on a case by case basis.

iiii) Efficiency of return to recipient parent. [START_REF] Hospital | Marker-assisted introgression of quantitative trait loci[END_REF] stated that after three cycles of backcross the gain in return to recipient parent is limited only to carrier chromosomes. Moreover more cycles could also lead to the loss of QTL donor alleles. [START_REF] Thabuis | Comparative mapping of Phytophthora resistance loci in pepper germplasm: evidence for conserved resistance loci across Solanaceae and for a large genetic diversity[END_REF] showed that after 3 cycles of back cross for introgressing resistance QTLs to Phytophtora capsici, non donor segment remained on the non-carrier chromosomes. In addition, a limited return to recipient parent was observed for carrier chromosomes, which was mainly due to the limit number of plants used for the foreground selection step.

Moreover a better knowledge in genome organization is required as unfavourable linkages among traits and recombination between markers and QTLs could be present, which are responsible of the limited effective return to the genome of recipient parent.

v) Limits linked to the inbreed populations which generally show a low level of molecular markers polymorphism. To better apply the MAS strategy, QTLs analysis among different populations which derive from different crosses should be used to detect favourable alleles from different parents. Thus a population will be created with the target of including the totality of favourable alleles (Ribaut and Betran, 1999).

Objectives of thesis

Up to know, pepper molecular genetic linkage maps have all been based on a rather low number of individuals per progeny (commonly between 40 and 100, rarely up to 200), resulting in a poor level of resolution [START_REF] Lefebvre | Molecular Markers for Genetics and Breeding: Development and Use in Pepper (Capsicum spp.)[END_REF]). As the resolution of a genetic map depends on the number of recombination events in the population, improvement can be achieved by increasing either the number of individuals and generations and/or the number of markers used to identify recombination events.

Mapping in a single population generates a more reliable and accurate map than an integrated map derived from independent mapping populations. In summary, the aims of the thesis are:

CONCERNING THE HORTICULTURAL

• To develop a new set of SSR markers from genic Capsicum spp. DNA sequence, extending the set reported by Nagy et al. (2004), and describe the potential utility of these assays for the development of high-resolution integrated genetic maps in pepper

• To construct a high resolution genetic linkage map in pepper.

• To perform fine mapping of QTLs linked to horticultural traits using the new genetic linkage map, and confirm the position of QTLs detected by comparing QTLs analysis performed on two different populations.

• To evaluate the effects of the reduction of the size of the population on mapping, trait distribution and QTL detection.

• To examine by different genetic linkage maps, macro-synteny among Solanaceae species.

• To integrate information of genetic locus for resistances and horticultural traits. (or simple sequence repeats, SSRs) are particularly valuable because of their co-dominant, multi-allelic nature (Gupta et al. 1996) and their ready adaptation to automated separation and detection platforms [START_REF] Nicot | Study of simple sequence repeat (SSR) markers from wheat expressed sequence tags (ESTs)[END_REF]. SSRs are abundant and hypervariable in all genomes examined to date [START_REF] Tautz | Simple sequences are ubiquitous repetitive components of eukaryotic genomes[END_REF][START_REF] Tautz | Hypervariability of simple sequences as a general source for polymorphic DNA markers[END_REF][START_REF] Powell | Polymorphism revealed by simple sequence repeats[END_REF]Toth et al. 2000, Kumpatla and[START_REF] Kumpatla | Mining and survey of simple sequence repeats in expressed sequence tags of dicotyledonous species[END_REF]. At present about 180

pepper SSRs are available in the public domain, but only some of these have been either inter-or intraspecifically mapped [START_REF] Lee | Characterization and molecular genetic mapping of microsatellite loci in pepper[END_REF][START_REF] Barchi | A high-resolution intraspecific linkage map of pepper (Capsicum annuum L.) and selection of reduced RIL subsets for fast mapping[END_REF][START_REF] Minamiyama | An SSR-based linkage map of Capsicum annuum[END_REF]. However, none were included in a recently published integrated 2,262 locus genetic map [START_REF] Paran | An integrated genetic linkage map in pepper (Capsicum spp.)[END_REF], derived from the analysis of six distinct populations.

The further development of pepper SSRs will therefore be valuable as a tool to facilitate mapping in this species.

Conventionally, the development of SSR markers requires the screening of genomic libraries, which may or may not have been previously enriched with SSR-containing fragments [START_REF] Zane | Strategies for microsatellite isolation: a review[END_REF]. In recent years, alternative strategies have been developed, in particular by combining the concept of AFLP and the microsatellite-anchor primer technique [START_REF] Hayden | Sequence-tagged microsatellite profiling (STMP): a rapid technique for developing SSR markers[END_REF][START_REF] Yang | DNA fingerprinting based on microsatellite-anchored fragment length polymorphisms, and isolation of sequence-specific PCR markers in lupin (Lupinus angustifolius L.)[END_REF][START_REF] Hayden | Sequence tagged microsatellite profiling (STMP): improved isolation of DNA sequence flanking target SSRs[END_REF][START_REF] Albertini | Microsatellite-AFLP for genetic mapping of complex polyploids[END_REF]Acquadro et al. 2005aAcquadro et al. , 2005b)). However, the increasing public availability of genic DNA sequences provides an substitute route for SSR marker development (Varshney et al. 2005), which was pioneered in the model plant Arabidopsis thaliana [START_REF] Cardle | Computational and experimental characterization of physically clustered simple sequence repeats in plants[END_REF] and subsequently extended to a range of crop species including barley, maize, durum wheat, rye, sugarcane and grape [START_REF] Chin | Maize simple repetitive DNA sequences: abundance and allele variation[END_REF][START_REF] Scott | Analysis of SSRs derived from grape ESTs[END_REF][START_REF] Temnykh | Mapping and genome organization of microsatellite sequences in rice (Oryza sativa L.)[END_REF][START_REF] Cordeiro | Microsatellite markers from sugarcane (Saccharum spp.) ESTs cross transferable to erianthus and sorghum[END_REF][START_REF] Eujayl | Isolation of EST-derived microsatellite markers for genotyping the A and B genomes of wheat[END_REF][START_REF] Hackauf | Identification of microsatellite polymorphisms in an expressed portion of the rye genome[END_REF][START_REF] Sharopova | Development and mapping of SSR markers for maize[END_REF][START_REF] Saha | A molecular linkage map of a tall fescue population segregating for forage quality traits[END_REF][START_REF] Thiel | Exploiting EST databases for the development and characterization of genederived SSR-markers in barley (Hordeum vulgare L.)[END_REF][START_REF] Qureshi | EST-SSR: a new class of genetic markers in cotton[END_REF]. By applying this approach to a collection of some 23,000 Capsicum sequences, Nagy et al. (2004) succeeded in developing a set of 50 polymorphic SSRs.

It has been suggested that the frequency of SSRs is inversely related to genome size and to the proportion of repetitive DNA, but its frequency in the gene space (and particularly in the untranslated regions) is independent of genome size [START_REF] Morgante | Microsatellites are preferentially associated with non repetitive DNA in plant genomes[END_REF]. From an analysis of more than 1.5 million EST sequences derived from 55 dicotyledonous species, [START_REF] Kumpatla | Mining and survey of simple sequence repeats in expressed sequence tags of dicotyledonous species[END_REF]

2005).

In this chapter is reported on the development of a new set of SSR markers from genic Capsicum spp. DNA sequence, extending the set reported by [START_REF] Nagy | Occurrence and polymorphism of microsatellite repeats in the sequence databases in pepper[END_REF], and the potential utility of these assays for the development of high-resolution integrated genetic maps in pepper is described.

Material and methods

In silico detection of SSR-containing sequences

Since the sequence survey conducted by [START_REF] Nagy | Occurrence and polymorphism of microsatellite repeats in the sequence databases in pepper[END_REF] [START_REF] Altschul | Gapped BLAST and PSI-BLAST: a new generation of protein database search programs[END_REF]. First, polyA and polyT tracts were removed, leaving no (T) 10 or (A) 10 in any 10bp window at either end of the sequences. SSR-containing sequences were identified using MISA software, a Perl script [START_REF] Thiel | Exploiting EST databases for the development and characterization of genederived SSR-markers in barley (Hordeum vulgare L.)[END_REF] which allows both perfect and compound SSRs to be detected. We considered as an SSR any sequence where a repeat motif of one to six nucleotides in length was repeated at least ten times (mononucleotide motif), six times (dinucleotides) or five times (higher-order motifs). For compound repeats, the maximum default interruption (spacer) length was set at 100bp. Redundant sequences were filtered by BLAST analysis, using each individual sequence as a query against the total set of selected sequences. Homologous sequences were aligned using ClustalW (Thompson et al. 1994) and scanned manually in the sequence editor window of the GDE (Genetic Data Environment, version 2.2) package. The criteria for redundancy were (i) where a cluster contained two or more identical sequences, the longest was retained; (ii)

where the members of a cluster fell into recognisable sub-groups, one member of each sub-group was retained; (iii) sequences which were composed entirely of SSR motif, lacking any flanking sequence, were discarded since their uniqueness cannot be established and in any event, primer design is not possible. The filtered set were again subjected to BLAST against all available Capsicum SSR-containing sequences [START_REF] Huang | Development of pepper SSR markers from sequence databases[END_REF][START_REF] Lee | Characterization and molecular genetic mapping of microsatellite loci in pepper[END_REF][START_REF] Nagy | Occurrence and polymorphism of microsatellite repeats in the sequence databases in pepper[END_REF]

Primer design

Primer pairs were designed from the flanking sequences, using PRIMER3 (Rozen and Skaletzky 2000) in batch mode via the p3_in.pl and p3_out.pl Perl5 scripts within the MISA package. The target amplicon size was set to 100 -300bp, the optimal annealing temperature to 60°C, and the optimal primer length to 20bp. Where amplification was unsuccessful, alternative primers were designed by manual input into PRIMER3, using a relaxation of the default parameters. Newly developed SSR markers were given the prefix EPMS (EST Pepper MicroSatellites) attached to a number starting from 595.

Plant material

The PCR amplification of EST-SSR products, and the initial polymorphism screen were carried out using a set of DNA templates extracted from four C. annuum ('P4', 'GF109', 'YW' and 'CM334') and one C. frutescens ('Tabasco') accession. These genotypes were chosen because they have been used as parents in our three mapping populations ('Tabasco' x 'P4', 'GF109' x 'CM334' and 'YW' x 'CM334').

SSRs displaying polymorphism were subsequently tested against a second DNA panel, containing two annuum and nine wild Capsicum spp.

genotypes (Table 1). Genomic DNA was isolated from young leaves following [START_REF] Dellaporta | A plant DNA minipreparation: version II[END_REF].

PCR conditions and the detection of SSR amplicons

Data analysis

A marker's PIC (polymorphism information content) value reflects the number of alleles and their distribution within a population [START_REF] Bonnet | Phytophthora resistance QTLs in pepper present colinearities with late blight resistance loci in potato and tomato[END_REF]. For our purposes, it was estimated using the equation given by [START_REF] Anderson | Optimizing parental selection for genetic linkage maps[END_REF]:

where Pij is the frequency of the ith allele for marker i and the summation extends over n alleles, calculated for each SSR locus.

The EST-SSR products from the 16 test genotypes were scored as band presence (1) and absence (0), thus generating a binary matrix. The binary data matrix was used to compute pair-wise similarity coefficients (Nei and Li 1979), and the similarity matrices obtained were utilized to construct a UPGMA-based dendrogram [START_REF] Sneath | The Pun1 gene for pungency in pepper encodes a putative acyltransferase[END_REF]. The analyses were performed within the software package NTSYS-PC version 2.10 (Rohlf 2002).

Results and discussion

SSR frequency and distribution

The in silico analysis identified 1,325 SSRs in 899 (11%) of the 8,094

Capsicum sequences. Two or more SSR motifs were present in 298 (33%) of these 899 sequences, including 164 cases of compound SSRs, according to the criteria applied (Table 2). This SSR density (one per 3.1Kbp) is about double that estimated across the cereals (barley, maize, rice, rye, sorghum and wheat - Varshney et al. 2002). Inter-SSR distances are typically highly species-specific, ranging from 3.4Kbp in rice to 11.1Kbp in tomato [START_REF] Cardle | Computational and experimental characterization of physically clustered simple sequence repeats in plants[END_REF]. The efficiency of SSR identification depends on the criteria applied, and the type of SSR motif.

Our higher success rate of SSR identification probably reflects the less stringent than normal length criterion adopted. Furthermore, as di-, triand tetra-nucleotide motifs are those most commonly targeted for marker development, most analyses to date have ignored mononucleotide motifs [START_REF] Kantety | Data mining for simple sequence repeats in expressed sequence tags from barely, maize, rice, sorghum and wheat[END_REF][START_REF] Eujayl | Medicago truncatula EST-SSRs reveal cross-species genetic markers for Medicago spp[END_REF]Saha et al. 2004;[START_REF] Park | Genetic mapping of new cotton fiber loci using EST-derived microsatellites in an interspecific recombinant inbred line cotton population[END_REF][START_REF] Chen | Mining and characterizing microsatellites from citrus ESTs[END_REF][START_REF] Han | Characteristics, development and mapping of Gossypium hirsutum derived EST-SSRs in allotetraploid cotton[END_REF]. However, we have included this class, as they have proven useful for filling gaps in linkage maps constructed from di-, tri and tetra-nucleotide SSRs [START_REF] Kumpatla | Mining and survey of simple sequence repeats in expressed sequence tags of dicotyledonous species[END_REF].

Seven large sequences (the 104Kbp YAC clone AY702979, and six genomic or full-length cDNA sequences representing known genes - et al. 2000;[START_REF] Scott | Analysis of SSRs derived from grape ESTs[END_REF][START_REF] Temnykh | Mapping and genome organization of microsatellite sequences in rice (Oryza sativa L.)[END_REF][START_REF] Morgante | Microsatellites are preferentially associated with non repetitive DNA in plant genomes[END_REF]Varshney et al. 2002;[START_REF] Thiel | Exploiting EST databases for the development and characterization of genederived SSR-markers in barley (Hordeum vulgare L.)[END_REF]. It has been hypothesised that this feature has evolved as a result of the suppression of non-trimeric SSRs, as variation in the repeat number of these SSRs will frequently result in frameshift mutations [START_REF] Metzgar | Selection against frameshift mutation limits macrosatellite expansion in coding DNA[END_REF] -unlike the situation for trinucleotide SSRs, where repeat unit variation does not normally disturb frameshift.

The occurrence of the various SSR motifs is summarized in Table 3. The frequency of a given SSR type is of interest not only to allow a better understanding of genome structure to be gained, but also provides a guide to increase the efficiency of SSR development [START_REF] Kumpatla | Mining and survey of simple sequence repeats in expressed sequence tags of dicotyledonous species[END_REF]. Among the dimeric SSRs, the most abundant motif was GA/CT (58%), similar to the situation pertaining in a wide array of species [START_REF] Temnykh | Mapping and genome organization of microsatellite sequences in rice (Oryza sativa L.)[END_REF][START_REF] Kantety | Data mining for simple sequence repeats in expressed sequence tags from barely, maize, rice, sorghum and wheat[END_REF][START_REF] Thiel | Exploiting EST databases for the development and characterization of genederived SSR-markers in barley (Hordeum vulgare L.)[END_REF]Fraser et al. 2004;[START_REF] Nicot | Study of simple sequence repeat (SSR) markers from wheat expressed sequence tags (ESTs)[END_REF][START_REF] Saha | Tall fescue EST-SSR markers with transferability across several grass species[END_REF][START_REF] Kumpatla | Mining and survey of simple sequence repeats in expressed sequence tags of dicotyledonous species[END_REF]. The CG motif was absent.

Dinucleotide motifs are present in a number of codons -for example, GA/CT occurs in (GAG) n , (AGA) n , (UCU) n and (CUC) n , translating into polyArg, Glu, Ala and Leu respectively. Ala and Leu are present in polypeptides at frequencies of 8% and 10%, respectively [START_REF] Lewin | Genes V[END_REF], providing one of the major reasons why GA/CT motifs are present at such high frequencies in EST collections [START_REF] Kantety | Data mining for simple sequence repeats in expressed sequence tags from barely, maize, rice, sorghum and wheat[END_REF]. AT SSRs are typically abundant in plant genomic sequence [START_REF] Lagercrantz | The abundance of various polymorphic microsatellite motifs differs between plants and vertebrates[END_REF][START_REF] Morgante | PCR-amplified microsatellites as markers in plant genetics[END_REF], and they are also well represented among the pepper EST sequences (26% of the dimeric motifs, Table 3); in contrast, they are under-represented in barley [START_REF] Thiel | Exploiting EST databases for the development and characterization of genederived SSR-markers in barley (Hordeum vulgare L.)[END_REF], rice [START_REF] Temnykh | Mapping and genome organization of microsatellite sequences in rice (Oryza sativa L.)[END_REF] and maize [START_REF] Chin | Maize simple repetitive DNA sequences: abundance and allele variation[END_REF].

AAG/CTT was the most common trimeric motif present in pepper, and AAAT/ATTT the most common tetrameric one (Table 3). AAG repeats are common in both A. thaliana [START_REF] Cardle | Computational and experimental characterization of physically clustered simple sequence repeats in plants[END_REF] and Gossypium spp. [START_REF] Park | Genetic mapping of new cotton fiber loci using EST-derived microsatellites in an interspecific recombinant inbred line cotton population[END_REF], while CCG predominates in barley, rice, maize, sorghum and sugarcane [START_REF] Temnykh | Mapping and genome organization of microsatellite sequences in rice (Oryza sativa L.)[END_REF][START_REF] Cordeiro | Microsatellite markers from sugarcane (Saccharum spp.) ESTs cross transferable to erianthus and sorghum[END_REF][START_REF] Kantety | Data mining for simple sequence repeats in expressed sequence tags from barely, maize, rice, sorghum and wheat[END_REF][START_REF] Thiel | Exploiting EST databases for the development and characterization of genederived SSR-markers in barley (Hordeum vulgare L.)[END_REF][START_REF] Nicot | Study of simple sequence repeat (SSR) markers from wheat expressed sequence tags (ESTs)[END_REF], and AAC in wheat [START_REF] Kantety | Data mining for simple sequence repeats in expressed sequence tags from barely, maize, rice, sorghum and wheat[END_REF]. Presumably, these differences vary across genomic regions (coding or non-coding) and/or different organisms [START_REF] Park | Genetic mapping of new cotton fiber loci using EST-derived microsatellites in an interspecific recombinant inbred line cotton population[END_REF], but it is difficult to compare the prevalence of a particular motif across different plant species due to the use of mutually inconsistent search and retention criteria by different studies.

Table 4 summarises the properties of the 783 SSR loci present in nonredundant sequences, classified on the basis of repeat motif and number of repeat units. Most of trimeric (84%) and dimeric (65%) SSRs showed 5-6 or 6-7 repeats, respectively, consistent with the mean size of barley EST-SSRs [START_REF] Thiel | Exploiting EST databases for the development and characterization of genederived SSR-markers in barley (Hordeum vulgare L.)[END_REF], and with range recorded among the 55 dicotyledonous species by [START_REF] Kumpatla | Mining and survey of simple sequence repeats in expressed sequence tags of dicotyledonous species[END_REF].

The cluster analysis showed that 44 of the 576 non-redundant SSR-containing sequences were highly similar to those exploited previously [START_REF] Nagy | Occurrence and polymorphism of microsatellite repeats in the sequence databases in pepper[END_REF][START_REF] Lee | Characterization and molecular genetic mapping of microsatellite loci in pepper[END_REF], and so 532 sequences (6.6% of the original sequences) were taken forward for the development of new SSR markers. The seven long sequences (>1.5Kbp) were manually screened for SSR motifs, generating 57 SSRs, 39 of which contained mononucleotide and 12 dinucleotide repeats.

Among the latter, AT was the most common motif, and CG repeats were totally absent (Table 3). From the 348 pepper SSRs developed, a subset of 204 primer pairs were finally selected for a polymorphism survey, by applying a minimum repeat length criterion of 18 repeats for poly(A) and poly(T) mononucleotides, and seven for all dinucleotides. This subset comprised 28 mononucleotide and 20 dinucleotide while all the higher-order and compound repeats were included.

SSR-marker development

Evaluation of marker polymorphism

The initial survey of the five mapping parents showed that dinucleotide motifs, although under-represented, were more informative than the trinucleotide repeats. A low variability of trimeric EST-SSR loci has also been demonstrated in both rice [START_REF] Cho | Diversity of microsatellites derived from genomic libraries and GenBank sequences in rice (Oryza sativa)[END_REF] and pine [START_REF] Liewlaksaneeyanawin | Single-copy, species-transferable microsatellite markers developed from loblolly pine ESTs[END_REF]). The 49 EST-derived SSR-markers useful for genetic mapping are presented in Table 5; 47 of these detect polymorphism between 'Tabasco' and 'P4' and are thus suitable for interspecific mapping, while 21 are mappable in both intra-specific populations. Overall, 49% of the polymorphic markers were mappable in one population, 18% in two and 31% in all three mapping populations.

Amplicons of expected size were obtained in 80% of cases. In five cases, however, larger than expected amplicons were generated, presumably the outcome of interruption by intronic sequence; while in the remaining five cases, a smaller than expected amplicon was generated. This unexpected result has been suggested by [START_REF] Nicot | Study of simple sequence repeat (SSR) markers from wheat expressed sequence tags (ESTs)[END_REF] to be generated by a combination of (1) the occurrence of deletions within the genomic sequence;

(2) a lack of priming specificity, resulting in the amplification of a non-target member of a gene family; or

(3) the presence of minor sequence variation between the amplified copy and the consensus sequence.

The PIC value of each of the 49 mappable markers was based on the allelic constitution of all 16 templates (Table 1). The number of alleles and the range in allele size are reported in [START_REF] Scott | Analysis of SSRs derived from grape ESTs[END_REF]. This conservation may act to inhibit the level of intraspecific polymorphism present -thus it was unsurprising to find that only 24% of the ESTderived SSRs were informative in the interspecific mapping populations.

This level of polymorphism is typical of other species [START_REF] Eujayl | Isolation of EST-derived microsatellite markers for genotyping the A and B genomes of wheat[END_REF]Han et al. 2004;[START_REF] Park | Genetic mapping of new cotton fiber loci using EST-derived microsatellites in an interspecific recombinant inbred line cotton population[END_REF], and compares poorly with the rate achievable from SSR assays derived from sequence extracted from enriched genomic DNA libraries (Reddy et al. 2001;[START_REF] Eujayl | Isolation of EST-derived microsatellite markers for genotyping the A and B genomes of wheat[END_REF][START_REF] Nguyen | Wide coverage of the tetraploid cotton genome using newly developed microsatellite markers[END_REF]).

Diversity analysis

The usefulness in the context of diversity analyses of the derived EST-SSR markers was investigated by assessing genetic similarity (GS)

among the 16 test genotypes. GS varied from 0.09 ('Tabasco' vs.

'CM334') to 0.81. ('Chi1' vs. 'Chi7'). Genetic relationships between the accessions was in good agreement with known taxonomic classifications. Thus C. annuum types were clustered together, and two sub-clusters corresponding to fruit morphology characteristics could be recognised -the small-fruited types ('Perennial','MN1' and 'CM334') being clearly separated from the large-fruited ones. The cluster closest to the annuum group contained both frutescens and chinense types, consistent with the taxonomic model which groups these three species into a single complex [START_REF] Pickersgill | The genus Capsicum: a multidisciplinary approach to the taxonomy of cultivated and wild plants[END_REF]). The third cluster contained the remaining wild Capsicum species baccatum (vars. baccatum and pendulum), praetermissum, chacoense, eximium and pubescens (Figure 1). [START_REF] Thiel | Exploiting EST databases for the development and characterization of genederived SSR-markers in barley (Hordeum vulgare L.)[END_REF] have stressed some limitations of the application of SSR markers for diversity studies, emphasising the possibility of homoplasy (identical allele sizes may not be identical by descent), and pointing out that alleles of different size can be generated by indel events, as well as by variation in the number of SSR repeats. However, the SSR marker-based genetic relationships among the Capsicum species reported here are in agreement to those generated by RFLP, RAPD and AFLP markers [START_REF] Prince | A survey of DNA polymorphism within the genus Capsicum and the fingerprinting of pepper cultivars[END_REF]Rodriguez et al. 1999;[START_REF] Portis | Multivariate analysis of genetic relationships between Italian pepper landraces[END_REF].

Conclusion

This study was designed to supplement ongoing efforts to develop and exploit EST-SSRs in pepper [START_REF] Huang | Development of pepper SSR markers from sequence databases[END_REF][START_REF] Lee | Characterization and molecular genetic mapping of microsatellite loci in pepper[END_REF]Nagy et al. 2004). The newly-derived EST-SSRs are informative for phylogenetic and mapping studies. Since EST-SSRs are present within the transcriptome, these assays may represent a valuable means to map and identify genes of known function related to phenotypic variation.

Table 1 Capsicum accessions assayed for the study of EST-SSR variation.

detected polymorphism in sample panel 1 were tested further using DNAs from both sample panels to calculate PIC values. markers distributed over all 12 chromosomes were screened. In most cases, the markers were correctly assigned to their expected chromosome, but the accuracy of the map position decreased as the number of individuals was reduced.

.

Introduction

Cultivated Capsicum is native to Central and South America [START_REF] Pickersgill | Cytogenetics and evolution of Capsicum L[END_REF], and includes the species chinense, baccatum, frutescens, pubescens and annuum. The latter, of Mexican origin, is globally the most widely grown species, and is used as a source of spice and colorant, as a vegetable, and has some medical applications. The species is divided into large-fruited bell peppers and small pungent types (Bosland and Votava 2000). It is diploid, with a somatic chromosome number of 24, its haploid DNA content is 2.76 pg and its genome size is between 2702 and 3420 Mbp (Arumuganathan and Earle 1993;Galbraith et al. 1983,). Linkage maps have been constructed using both intraspecific annuum populations [START_REF] Lefebvre | Construction of an intraspecific integrated linkage map of pepper using molecular markers and doubled haploid progenies[END_REF]Ben Chaim et al. 2001;[START_REF] Ogundiwin | Construction of 2 intraspecific linkage maps and identification of resistance QTLs for Phytophthora capsici root-rot and foliar-blight diseases of pepper (Capsicum annuum L.)[END_REF][START_REF] Sugita | Rapid construction of a linkage map using High-efficiency Genome Scanning/AFLP and RAPD , Based on an Intra-specific, Doubledhaploid Population of Capsicum annuum[END_REF] and interspecific crosses, such as annuum x chinense [START_REF] Livingstone | Genome mapping in capsicum and the evolution of genome structure in the Solanaceae[END_REF]1999;Kang et al. 2001) and annuum x frutescens (Rao et al.2003;[START_REF] Sasvári | Construction of a new inter-specific genetic map in pepper based on AFLP and microsatellite markers[END_REF]). Interspecific crosses benefit from a high level of marker polymorphism, but suffer from low fertility, segregation distortion, and major structural rearrangements [START_REF] Tanksley | Linkage relationships and chromosomal locations of enzyme-coding genes in pepper, Capsicum annuum[END_REF]Iglesias 1984, Lanteri 1991;[START_REF] Lanteri | Chromosomal structural changes in Capsicum annuum L. and Capsicum chinense[END_REF], which limit the power of the linkage analysis and restrict their relevance to marker-assisted selection applications [START_REF] Lefebvre | Towards the saturation of the pepper linkage map by alignment of three intraspecific maps including known-function genes[END_REF]). An integrated map, based on six populations and consisting of 2262 markers covering 1832 cM, has recently been assembled [START_REF] Paran | An integrated genetic linkage map in pepper (Capsicum spp.)[END_REF]). This has achieved a greatly improved average marker density and better genome coverage. However, confidence in marker position and order remains low, particularly with regard to population-specific markers. Current pepper maps have all been based on a rather low number of individuals per progeny (commonly between 40 and 100, rarely up to 200), resulting in a poor level of resolution (Lefebvre 2005). As the resolution of a genetic map depends on the number of recombination events in the population, improvement can be achieved by increasing either the number of individuals per progeny and/or the number of markers used to identify recombination events. Mapping in a single population generates a more reliable and accurate map than an integrated map derived from independent mapping populations.

In the present paper, we describe the construction of a high resolution intraspecific genetic linkage map based on a single recombinant inbred line (RIL) population. The map position of highly reproducible, locusspecific, codominant PCR-based markers is of particular value for the integration of genetic information from different populations, and would underpin much applied research in pepper, including gene mapping, QTL analysis, and marker-assisted selection. Finally subsets of the most informative RILs were identified, in order to reduce the genotyping and phenotyping effort. A minimal set of lines was identified to map any new marker to a defined bin (a map segment delimited by recombination events) or to a specific chromosome.

Materials and methods

Plant material and DNA extraction

The RIL population was developed at INRA-Montfavet, France, by single seed descent, and comprised 297 F5 progeny from the cross 'Yolo Wonder' x 'Criollo de Morelos 334' (CM334). The parental lines were obtained at INRA-Avigon by 5 to 7 successive selfing from the original local cultivars to generate homozygous inbred lines. The former parent is an American bell pepper inbred line, and the latter a Mexican hot pepper inbred line, used as a source of resistance against Oomycetes (Phytophthora spp.) (Pochard and Daubèze 1980;Palloix et al. 1988Palloix et al. , 1990)), nematodes (Meloidogyne spp.) [START_REF] Djian-Caporalino | Spectrum of resistance to root-knot nematodes and inheritance of heat-stable resistance in pepper (Capsicum annuum L.)[END_REF]) and several viruses (Dogimont et al. 1996) The parents also differ from one another with respect to several key horticultural breeding traits. Seeds of the RIL progenies were obtained by selfing plants under an insect-proof tunnel to avoid outcrossing by insects. Total genomic DNA was extracted from young leaf tissue of each RIL and their parental lines according to CTAB method (Doyle and Doyle, 1990).. DNA quality was checked by 1% (w/v) agarose gel electrophoresis, and its quantity was assessed by ethidium bromide staining of an agarose gel loaded with DNA samples and DNA standard.

Molecular markers

Amplification fragment length polymorphisms (AFLPs)

AFLP reactions were performed as described by Vos et al. (1995), using 19 EcoRI/MseI, 11 PstI/MseI and 2 SacI/MseI primer combinations (PCs) (Table 1). The EcoRI, PstI and SacI primers were end-labelled with [γ-33 P] dATP to allow fragment visualisation by autoradiography.

Segregating markers were encoded by adding to the PC code a threedigit number reflecting the fragment's molecular weight.

Microsatellites (SSRs)

Forty SSRs were used for mapping purposes (Table 2). Of these, 31 were based on publicly available pepper EST sequences (19 as reported by [START_REF] Nagy | Occurrence and polymorphism of microsatellite repeats in the sequence databases in pepper[END_REF]Nagy et al. ( , 2006 in preparation) in preparation), and 12 to be published (Portis et al. unpublished)), with the remaining nine extracted from genomic libraries [START_REF] Lee | Characterization and molecular genetic mapping of microsatellite loci in pepper[END_REF]. PCR amplifications were performed in a 30µl volume containing 30ng genomic DNA as template as reported by [START_REF] Nagy | Occurrence and polymorphism of microsatellite repeats in the sequence databases in pepper[END_REF]. Forward primers were 5'-end labelled with FAM, JOE or NED for analysis on an ABI 3100 sequencer, and with Cy5 for the ALFExpressII platform. Polymorphisms were evaluated by the Genographer [START_REF] Benham | Genographer-AFLP/Microsatellite Software[END_REF] or by the ALFwin Fragment Analyser (Version 1.03, Amersham Pharmacia Biotech) programs.

Restriction fragment length polymorphisms (RFLPs)

The 19 RFLP probes used originated from a variety of sources, covering plant cDNAs, gDNAs and known-and unknown function gene sequences (Table 3). These were chosen to allow linkage group (LG) assignment to chromosomes and for ease of map alignment. RFLP procedures have been described elsewhere [START_REF] Lefebvre | Nuclear RFLP between pepper cultivars (Capsicum annuum L.)[END_REF].

Sequence tagged sites (STS)

The four STS markers comprised three converted from purified AFLP fragments and one linked to the Pvr4 resistance gene [START_REF] Caranta | Development of a CAPS marker for the Pvr4 locus: a tool for pyramiding potyvirus resistance genes in pepper[END_REF]. Amplicons were digested with the appropriate restriction enzyme (Table 3), before separation by 2% (w/v) agarose gel electrophoresis.

Sequence-specific amplication polymorphisms (SSAPs)

The technique first described by Waugh et al. (1997) and adapted by [START_REF] Tam | Comparative analyses of genetic diversities within tomato and pepper collections detected by retrotransposon-based SSAP, AFLP and SSR[END_REF] was employed. SSAP profiling was performed on a subset of 100 of the 297 RILs, using as PCs Tnt1-C00 and T135-E00.

For every dominant marker, the letter 'y' (Yolo Wonder) or 'c' (Criollo de Morelos 334) indicates the donor parent of the band.

Data analysis

A χ 2 goodness-of-fit test for 1:1 segregation was performed for each marker. Co-dominant markers were used to compare the observed and expected (6.25%) proportion of heterozygosity remaining at F5. Linkage analyses were generated from the RI model of Mapmaker/EXP version 3.0 [START_REF] Lander | MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations[END_REF]. LGs were determined with the "group" command, using as thresholds for linkage detection a minimum LOD of 8 and a maximum recombinant fraction (r) of 0.1. The sequence of commands was: (i) "order" to determine the most likely marker order within each LG; (ii) "ripple" to confirm marker order using a LOD of 3; (iii) "try" to identify the most likely position of unordered markers within their

LG; (iv) "genotype" to identify likely singletons. Putative singletons were checked by re-genotyping and, where necessary, correcting the scoring for markers flanking the apparent recombination event. Recombination fractions were converted into map distances with the Haldane mapping function [START_REF] Haldane | The mapping function[END_REF]. Ordered LGs were assigned to chromosome by alignment of markers present on prior maps [START_REF] Lefebvre | Towards the saturation of the pepper linkage map by alignment of three intraspecific maps including known-function genes[END_REF][START_REF] Paran | An integrated genetic linkage map in pepper (Capsicum spp.)[END_REF]. When several LGs where assigned to the same chromosome, "compare" was used to identify the most likely order. The merged groups were validated with "ripple" and a LOD of 3.

Choice of the most informative individuals

A number (26) of the RILs were removed from the population because of their poor fertility. From the remaining 271 individuals, two subpopulations "A" (141 individuals, i.e., about the half of the original population, and equivalent to one and one-half 96-well microtitre plates), and "B" (93 individuals, i.e., about one third of the original population, and equivalent to one 96-well microtitre plate) were formed with the help of the MapPop software package [START_REF] Brown | MapPop 1.0: Software for selective mapping and bin mapping[END_REF] using the full linkage map as the input file. Seven codominant markers (SSRs EPMS649, EPMS650, EPMS704, EPMS725, EPMS747 and EPMS755 and the STS ASCO02) were used to genotype subpopulation "A" and "B". Smaller subpopulations (ranging from 12 to 45 individuals) were developed in an attempt to define the smallest set of individuals which could chromosomally assign an additional marker. For this purpose, 13 chromosomally defined markers (e32/m55_114y, e44/m61_538c, p14/m39_453y, e44/m61_279y, e38/m61_203y, e31/m58_254c, e38/m60_401y, p17/m39_468c, EPMS310, e38/m60_227y, e31/m58_367y, e38/m60_212y, e43/m54_275c) were employed. The MapPop "sampleexp" command was used to select individuals with a high frequency of recombination events.

Results

Marker polymorphism and segregation

A total of 507 AFLPs ( from 'CM334'), and eight from Tnt1-C00 (five from 'Yolo Wonder', three from 'CM334'). Ninety SSR markers were assayed on DNAs of the parents and their F1; 40 were polymorphic and thus suitable for mapping (Table 2).

Codominant markers allowed the observed level of heterozygosity to be assessed. A significant excess of heterozygosity was detected at nine loci (maximum 18.7%), and a deficit at three loci (minimum 0% LG and placed with the Mapmaker command "try" and (iii) those that were unlinked. As reported in Figure 1, the proportion of skewed markers assigned to the framework map and those placed with the command "try" decreased with the P-value, while in contrast, the proportion of skewed unlinked markers increased as the P-value was reduced. Finally, 24 skewed markers were placed on the framework map, of which 17 were linked to chromosomes (Figure 2).

Construction of the linkage map and chromosomal assignment

The linkage map was formed from 587 markers ( 507 LGs, carrying 69% of the markers, were allocated to one of the twelve pepper chromosomes (Figure 2). The coverage of this map was

Identification of the most informative individuals

The most genetically informative individuals were identified from the two subpopulations "A" (141 individuals) and "B"(93 individuals) to accelerate further mapping. The mean bin size increased from 0.55 cM in the whole RIL population to 0.82 and 1.12 in, respectively, the "A" and "B" subpopulations. Seven further codominant markers were successfully assigned to LGs. Thus, the STS locus ASCO02 was incorporated into the framework map using the "order" command, while six SSRs were successfully placed by the command "try". By using the subpopulation "B", these markers mapped to the same LGs but with a lower precision, as a unique marker position could not be identified. The thirteen markers assigned to the 12 chromosomes used to scan the series of smaller subpopulations (12, 24, 29 or 45 individuals) were subjected to the "group" command with a LOD score of 3 and an r value of 0.1. This process allowed for the successful mapping of three (subpopulation size = 12), eight (24), 10 (29) and all 13 (45) markers to their respective expected LGs.

Discussion

Molecular markers and map construction

Our aim was to construct a high resolution genetic linkage map of pepper, using a RIL population derived from an intraspecific cross of C.

annuum. This population is of high relevance to the gene pool used by pepper breeders and should reduce the frequency of skewed segregation, and thereby increase the mapping precision. However, due to the low level of polymorphism (around 40%, see also [START_REF] Lefebvre | Nuclear RFLP between pepper cultivars (Capsicum annuum L.)[END_REF][START_REF] Lefebvre | Evaluation of genetic distances between pepper inbred lines for cultivar protection purposes: comparison of AFLP, RFLP and phenotypic data[END_REF], an extensive genotyping effort was required. The final map has a good level of resolution both because the population is larger than ever used in pepper, and because the use of an F5 generation allowed more meioses to be involved than in the previous F2 or doubled haploid populations. With the 297 RILs, the mapping precision is 0.17cM (r=R/(2-2R) with R=1/297) compared to 0.34 cM [START_REF] Lefebvre | Construction of an intraspecific integrated linkage map of pepper using molecular markers and doubled haploid progenies[END_REF] for a similarly sized DH population. Because of the high percentage of homozygosity, an immortalised RIL population allows for the replication of phenotypic assays across different environments to supply robust estimates of trait means, thus making the identification of quantitative trait loci more efficient and reliable.

About 14% of the markers showed distorted segregation ratios -higher than the 7% to 10% previously reported in the intraspecific maps of [START_REF] Lefebvre | Towards the saturation of the pepper linkage map by alignment of three intraspecific maps including known-function genes[END_REF] and [START_REF] Sugita | Rapid construction of a linkage map using High-efficiency Genome Scanning/AFLP and RAPD , Based on an Intra-specific, Doubledhaploid Population of Capsicum annuum[END_REF], but considerably lower than levels reported in interspecific maps [START_REF] Livingstone | Genome mapping in capsicum and the evolution of genome structure in the Solanaceae[END_REF][START_REF] Kang | An interspecific (Capsicum annuum × C. chinense) F2 linkage map in pepper using RFLP and AFLP markers[END_REF]). Although about 90% of the distortion observed in doubled haploid populations generated with 'CM334' as a parent involved a deficit of 'CM334' alleles) [START_REF] Lefebvre | Construction of an intraspecific integrated linkage map of pepper using molecular markers and doubled haploid progenies[END_REF], however, more markers were skewed towards 'CM334' than towards 'Yolo Wonder' in the RIL progeny. A possible cause for this inconsistency is that 'CM334' is strongly recalcitrant to in vitro androgenesis (unpublished data), and thus its use here as a parent of a single seed descent-derived population avoids any in vitro selection against 'CM334' alleles. The higher than expected level of heterozygosity may reflect selection against homozygosity for some 'CM334' alleles at some loci.

In order to increase confidence in marker placement, a stringent threshold was applied (LOD > 8 and r < 0.1). This resulted in the definition of 49 LGs, of which 21 included only a limited number of loci, and presumably will be merged into larger groups with the addition of further markers. The application of less restrictive conditions allows the generation of fewer LGs, but significantly decreases the level of confidence. One large LG carrying markers known to be located on distinct chromosomes was found at r<0.2. Unassigned LGs, together with some unlinked markers, could be associated with various chromosomes at a LOD < 8 and r > 0.1, but their position and order was not precisely determinable, and thus they were not placed on the framework map. About 55% of the whole marker set was usable as framework markers, as their map order was confirmed at LOD > 3.0.

The framework markers were evenly spaced, although some clustering was evident on chromosomes P5, P9 and P11. Clustering is a common phenomemon, particularly, although not exclusively, in centromeric regions. It is thought to arise as a result of an inhibition of recombination in these regions [START_REF] Boersma | Construction of a genetic linkage map using MFLP and identification of molecular markers linked to domestication genes in narrow-leafed lupin (Lupinus angustifolius L.)[END_REF] The overall length of the map is 1857 cM, similar to the 1832 cM reported for the integrated map of [START_REF] Paran | An integrated genetic linkage map in pepper (Capsicum spp.)[END_REF], but significantly greater than the 1466 cM reported recently by [START_REF] Ogundiwin | Construction of 2 intraspecific linkage maps and identification of resistance QTLs for Phytophthora capsici root-rot and foliar-blight diseases of pepper (Capsicum annuum L.)[END_REF] for a pepper map based on RILs.

The good genome coverage of the present map, calculated to be 86.5%, according to the method of [START_REF] Lange | How many polymorphic genes will it take to span the human genome?[END_REF], derives from the use of a large number of markers.

Map comparison

We have compared the framework map with those of Lefebvre et al. (2004), which corresponds to the lower part of the intraspecific chromosome P8.

IDENTIFICATION OF THE MOST INFORMATIVE RILS AND SELECTIVE GENOTYPING

As reported by [START_REF] Isidore | Toward a marker-dense meiotic map of the potato genome: lessons from linkage group I[END_REF], the larger the population, the greater the number of meioses upon which the map can be based, and so the greater the number of markers which can be ordered. However, the genotyping and phenotyping of large populations is costly. As a way of reducing this cost, we have sought to identify the most genetically informative individuals for further phenotypic and mapping studies. The MapPop software [START_REF] Brown | MapPop 1.0: Software for selective mapping and bin mapping[END_REF] is designed, on the basis of an already developed map, to identify optimized subpopulations which include the most informative individuals. Among the RILs, four subpopulations were identified, consisting of 141, 93, 45 or 29 individuals. When their potential for mapping was tested, both larger subpopulations delivered reasonable mapping precision, with a higher precision achieved when the largest subpopulation was genotyped. In the 45 individual subpopulation, the mean bin size increased to 2.00, and all of the 13 markers used for the test were precisely assigned to a chromosome. In the 29 individual subpopulation, the mean bin size increased to 2.83, and 10 out of the 13 markers were assigned to the expected chromosome, with an imprecise location within the chromosome. This rather small subset was identified to allow for a rapid screen of new markers and to assign them to a LG with the minimum of laboratory work, as proposed by [START_REF] Xu | Improving quantitative trait loci mapping resolution in experimental crosses by the use of genotypically selected samples[END_REF] LG24 LG19 e40/m49_207y# 0,0 p14/m39_117y LG24 LG33 p15/m43_178c# 0,0 p17/m39_330y 8,4

p25/m42_436c# 0,0 HPMS1_62
p25/m42_436c# 0,0 HPMS1_62
LG33

p15/m40_200y 0,0 p15/m40_209c 2,1
LG36

p15/m40_200y 0,0 p15/m40_209c 2,1
LG36

p15/m40_319c 0,0 EPMS_755 8,7
LG37

p15/m40_319c 0,0 EPMS_755 8,7
LG37 p17/m32_344c 0,0 p14/m41_132c 8,3

LG38 p17/m32_344c 0,0 p14/m41_132c 8,3

LG38 LG41 p19/m42_858y 0,0 p19/m42_874y 2,8

LG41 p25/m45_335c 0,0 p14/m39_345c 7,0

LG42 p25/m45_335c 0,0 p14/m39_345c 7,0

LG42 p14/m39_195c 0,0 p11/m49_105y 6,5

LG44 p14/m39_195c 0,0 p11/m49_105y 6,5

LG44 In this chapter the results on QTL analysis performed on 13 horticultural traits which control both fruit and plant characteristics are reported. The recombinant inbred population previously used to develop the genetic linkage map (chapter 2) was characterized for the horticultural traits. The QTL analysis was firstly performed in this whole progeny. Two other pepper populations originated from the crosses Perennial X Yolo

c33/m54_118c 0,0 EPMS_402
Wonder and H3 X Vania were analysed with the objective to explore the conservation or diversity of QTLs for horticultural traits in an enlarged pepper germplasm. Synteny analyses among related species, i.e.

pepper, tomato, potato and eggplant were also carried out for identifying conserved genomic regions which influence horticultural traits.

Lastly, in this chapter are reported the results of QTLs analysis carried out by using the two previously identified subpopulations (chapter 2) sampled from the large recombinant inbred progeny thanks to the application of the MapPop software [START_REF] Brown | MapPop 1.0: Software for selective mapping and bin mapping[END_REF].

Materials and Methods

Plant material and trait evaluation

The plant material consisted of three intra-specific populations developed from crosses between large fruited and sweet pepper inbred lines ('Yolo Wonder' or 'Vania') and small fruited pungent inbred lines derived from local cultivars from Mexico (CM334), India (Perennial) and

East Africa (H3) (Figure 1). These populations were developed at INRA-Montfavet, France, and were previously used for genetic analysis of disease resistance traits [START_REF] Daubèze | Resistance to Leveillula taurica in pepper (Capsicum annuum) is oligogeniccally controlled and stable in Mediterranean regions[END_REF], Lefebvre et al. 1995, Bonnet et al. submitted). The YC population included 297 recombinant inbred lines (RIL:F6) which were developed by selfing from the F5 RIL population used for map development and obtained by the F1 hybrid "Yolo Wonder" x "Criollo de Morelos 334" (CM334).

The PY population counted114 doubled haploids progeny derived from in vitro androgenesis of the F1 hybrid "Perennial" x "Yolo Wonder" . The HV population consisted of 101 doubled haploids progeny obtained from the F1 hybrid "H3" x "Vania".

For trait evaluation, the four parents, the F1 hybrids and their respective progenies were analysed. The experiments were arranged in a randomized complete block design with three replications. Each replication was constituted from 3 to 6 plants from each inbred or doubled haploid line, depending on the progeny. The parents and the F1 hybrids were also included as control genotypes in all the experiments.

A total of 13 horticultural key breeding traits were measured, which are also used as morphological descriptors of pepper accessions in international germplasm collection: (1) the mean fruit weight transformed into its logarithm value (Lfw), (2) the fruit length (Frl) -the distance (mm) from the pedicel attachment to the apex, (3) the fruit diameter (Frd) -the maximum fruit width (mm), (4) the fruit shape (Frs) -calculated by the ratio fruit length / fruit diameter, (5) the pericarp thickness (Pet) -(mm), ( 6) the number of fruit locules (Nlo), ( 7) the pedicel length (Pel) (mm), ( 8) the flowering earliness (Flw) -numbers of days from the sowing date to the anthesis of the first flower, (9) Axis length (Axl) -the length of the primary axis (cm) from the cotyledons to the first branching, (10) the number of leaves developed on the primary axis (between the cotyledons and first branching) (Nle), ( 11) the mean internode length (Inl) -the ratio of the total axis length to the number of leaves (cm), ( 12) the mean internode growth time (day) (Int) -the ratio of the flowering time minus 15 days (time necessary for cotyledon development) to the number of leaves and ( 13) the axis growth speed (Axs) (mm/day)which is the ratio of the axis length to the flowering time minus 15 days.

For the RILs-F6 progenies, data from all the 13 traits were available, while for the PY and the HV progenies, data for ten and eleven traits were available respectively (Table 1).

Yolo Wonder CM 334 Perennial

Vania H3

Figure 1: fruits of the pepper parental lines.

Data analyses

All statistical analyses were performed with the R software package (R Development Core Team 2006). Descriptive statistic analyses were performed to evaluate the goodness of the phenotypic data from the three populations: distribution analyses, median/mean/variance.

Analysis of variance (ANOVA) was applied to estimate genotypic/environmental effects according to the model where µ, b j , g i and e ij are the grand mean, block effect, genotype effect and error effect, respectively. Narrow-sense heritability (h 2 n ) values were calculated using the formula h 2 n = σ 2 A /( σ 2 A + σ 2 E /n) where σ 2 A is the genetic variance and σ 2 E is the environmental variance (including block, interaction and error effects) and n the number of repeats (blocks).

Pearson correlations between traits were estimated.

Map construction and QTL analyses

Genetic linkage maps used for QTLs analysis were the one previously reported in chapter 2 (Barchi et al. in press) for the F5YC progeny and the ones reported by [START_REF] Lefebvre | Towards the saturation of the pepper linkage map by alignment of three intraspecific maps including known-function genes[END_REF] for the PY and HV populations.

QTL analysis were performed with QTL Cartographer software [START_REF] Basten | QTL Cartographer[END_REF] using both interval mapping (IM) [START_REF] Lander | Mapping mendelian factors underlying quantitative traits using RFLP linkage maps[END_REF] and composite interval mapping (CIM) (Zeng,1994). A total of 1,000 permutations for both methods to establish empirical LOD thresholds at the 5% probability level [START_REF] Churchill | Empirical threshold values for quantitative trait mapping[END_REF] were performed. The proportion of observed phenotypic variation attributable to a particular QTL was estimated by the coefficient of determination (R 2 ). The total phenotypic variation explained was estimated by fitting a linear model (multiple regression) including all putative QTL for the respective trait simultaneously. For each QTL, the marker with the highest LOD was included as explicative variable in the multiple regression. Digenic interactions between all the markers of the core maps were tested with each trait using a two-way ANOVA, as described by [START_REF] Lefebvre | Both epistatic and additive effects of QTLs are involved in polygenic induced resistance to disease, a case study, the interaction pepper-Phytophthora capsici Leonian[END_REF]. Significant epistasis was retained when P<10 -6 .

QTLs were named as follow: the three first letters indicate the trait analysed. The first following number indicate the chromosome or the linkage group (LG) on which the QTL was detected and the second number indicate the position in which the QTL was identified in the studied progeny. QTLs bearing the same name in distinct progenies does not mean identity and will be further discussed. Finally the code IM (Interval Mapping) or CIM (Composite Interval Mapping) was added when QTLs were detected with a single of these 2 methods.

Choice of the most informative individuals in the YC population

A number (26) of the RILs were removed from the population because of their poor fertility. From the remaining 271 individuals, two subpopulations "A" (141 individuals, i.e., about the half of the original population), and "B" (93 individuals, i.e., about one third of the original population) were selected with the help of the MapPop software package [START_REF] Brown | MapPop 1.0: Software for selective mapping and bin mapping[END_REF] using the full linkage map as the input file (see chapter 2). The two subsets were tested for QTL mapping accuracy for three traits: (i) Lfw (logarithm of fruit weight), (ii) Axl (plant axis length) and (iii) Rec (receptivity) which is a component of resistance to Phytophthora capsici (data from Bonnet et al. Submitted).

Results

Phenotypic variation and trait correlations ii. Yolo Wonder X Criollo de Morelos population

Mean phenotypic values and narrow-sense heritability estimates for each trait in study are listed in Table 2. The large fruited Yolo Wonder produces blocky fruits which are heavier, longer, larger and with a thicker pericarp than the ones from Criollo the Morelos. The YW fruit shape was close to 1 while CM334 produced elongated fruits, its number of locules was always 4 while varied from to 2 to 3 for CM334. The pedicel length of both parents was similar. Considering plant traits, Yolo Wonder displayed a later flowering date, a shorter primary axis than CM334 but an analogous number of leaves on the axis; this resulted in a slower axis growth speed, a slightly shorter internode length and slightly slower internode growth time. The F6 progeny displayed normal-like distributions for all the traits (Figure 2). Most of the F6 inbred lines displayed intermediate values between the parental lines for all the fruit traits, except pedicel length for which transgressive phenotypes (ie. values outside of the parental range) were observed as the average value was higher than that both parental lines. Considering plant traits, the F6 inbred lines frequently displayed transgressive values, particularly when the parental values were close to each-other (number of leaves, internode length, internode growth time).

Heritability was high for each trait, ranging from 0.84 for the number of locules to 0.97 for fruit diameter and fruit shape (Table 2).

Strong positive or negative correlations were found between fruit traits as well as between plant traits (table 3), but no significant (p<0.05) or low correlation coefficient (<0.3) were detected between these two types of traits. The fruit weight increased with the fruit length, fruit diameter and pericarp thickness, and the fruit diameter with the pericarp thickness and the number of locules. A positive correlation was also detected between fruit length and pedicel length. Negative correlations were detected between the fruit shape and the pericarp thickness and the number of locules. Other correlations resulted from dependant variables (the fruit shape resulting from the ratio Frl/Frd). Considering plant traits, a late flowering date was associated with a high number of leaves developed on the axis and a long primary axis. One may also notice that a long axis and a high number of leaves was associated with a higher speed of axis growth (and a higher speed of internode growth). Table 3: Pearson correlation coefficient between traits measured in the F6 progeny. Traits analysed are logarithm of the mean fruit weight value (Lfw), the fruit length (Frl), the fruit diameter (Frd), the fruit shape (Frs), the pericarp thickness (Pet), the number of fruit locules (Nlo), the pedicel length (Pel), the flowering earliness(flw), Axis length (Axl), the number of leaves (Nle), the mean internode length (Inl), the mean internode growth time (Int) , the axis growth speed (Axs). Coloured boxes indicate significant correlations (P>0.05) 3).

Narrow sense heritability were high for all the traits, ranging from 0.87 for flowering time to 0.97 for fruit shape (Table 4).

As in the YC population a significant positive correlation was detected between fruit weight, length and diameter, as well as between the flowering time, axis length, number of leaves. Negative correlations were found for Axl and Int, Nle with Int and for Int and Axs.

Contrarily to the YC progeny, significant negative correlations (p<0.05)

were found between fruit and plant traits, particularly, the fruit weight, length and diameter were found to decrease when the lateness of flowering, the axis length and the number of leaves increased. (Table 3). Table 5: Correlation between traits in the PY population: Traits analysed are logarithm of the mean fruit weight value (Lfw), the fruit length (Frl), the fruit diameter (Frd), the fruit shape (Frs), the flowering earliness(flw), Axis length (Axl), the number of leaves (Nle), the mean internode length (Inl), the mean internode growth time (Int) , the axis growth speed (Axs).

Lfw

Coloured boxes indicate significant correlations (P>0.05)

iv. H3 X Vania population

Mean phenotypic values for each trait are listed in Table 6. Considering fruit traits, H3 produced narrow and elongated fruits with a thin flesh while fruits of Vania are large and with a heavier weight. However, contrarily to Yolo Wonder, Vania fruits are rather long with an oblate shape, resulting in a higher Frl/Frd ratio. Considering plant traits, flowering dates and internode length of Vania and H3 are very similar, but differences in the other traits are extreme with a much higher axis length and number of leaves, and a much more rapid stem and internode growth speed for H3 than Vania.

The HV progeny displayed normal-like distributions for all the traits. Most of the F6 inbred lines displayed intermediate values between the parental lines for all the fruit traits, except pedicel length for which the average value of the progeny was higher than both parental lines and inbred F6 lines displayed transgressive phenotypes. Considering plant traits, the HV progeny displayed transgressive values for flowering earliness and internode length as a consequence of very similar parental values (Figure 4).

Heritability was high for each trait, ranging from 0.77 for the internode length to 0.97 for fruit weight (Table 6).

As observed in the YC and PY progenies, positive significant correlations (p<0.05) were observed between fruit weight, length and diameter (pericarp thickness was not detected in this progeny). A late flowering date was associated with longer axis, higher number of leaves, and the speed of growth of the axis (and internode growth time)

increased with the number of leaves (and axis length). Similarly to the PY progeny, significant negative correlations (p<0.05) were found between fruit and plant traits, in particular, the fruit weight, length and diameter were found to decrease when the lateness of flowering, the axis length and the number of leaves increased. (Table 7). Figure 4: Frequency distribution for the 11 traits analysed in the HV population: logarithm of the mean fruit weight value (Lfw), the fruit length (Frl), the fruit diameter (Frd), the fruit shape (Frs), the pedicel length (Pel), the flowering earliness(flw), Axis length (Axl), the number of leaves (Nle), the mean internode length (Inl), the mean internode growth time (Int) , the axis growth speed (Axs). Parental mean values are designated H3 (H3), Vania (Vania) while F1 indicates the hybrid mean. Table 7 Pearson correlation coefficient between traits measured in the HV progeny. Traits analysed are: logarithm of the mean fruit weight value (Lfw), the fruit length (Frl), the fruit diameter (Frd), the fruit shape (Frs), the pedicel length (Pel), the flowering earliness(flw), Axis length (Axl), the number of leaves (Nle), the mean internode length (Inl), the mean internode growth time (Int) , the axis growth speed (Axs). Coloured boxes indicate significant correlations (P>0.05).

Lfw

Inl

125

QTL detection

A list of the QTLs detected for all traits in the 3 progenies is presented in figure 6 together with alignment of genetic maps from the 3 crosses.

Detailed data from each progeny are presented in the separate tables.

For each trait and progeny, the QTLs were declared as significant when their LOD values overpassed the threshold value equivalent to p=0.05 after 1000 permutations (see material and methods). QTLs reported included those founded with both IM and CIM but also those found with only IM or CIM.

Yolo Wonder X Criollo de Morelos population

Thirteen traits were analysed, and a total of 78 QTLs (Table 8) ranging from 2 to 12 per trait were identified. No significant digenic interactions were detectable (P<10 -6 ).

Logarithm of fruit weight

Seven QTLs were found, of which 5 detected with both methods, 1 with CIM and 1 with IM. Lfw3.1 and Lfw4.1 had the largest effect (R 2 = 0.11 and 0.15 respectively) and all QTLs detected explained the 48% of the total phenotypic variation. For all QTLs, the alleles from the large fruited variety Yolo Wonder increased fruit weight.

Fruit diameter

Twelve QTLs were found for this traits, of which 8 detected with both methods, 2 with IM and 2 with CIM. Frd11.1, Frd3.1 and Frd2.1CIM are the ones with most significant effects (R 2 = 0.13, 0,12 and 0,11 respectively) while the total phenotypic variability explained by all QTLs is equal to 91%. At all the QTLs the Yolo Wonder alleles contributed to increase the diameter of fruits.

Fruit shape

Eight QTLS were detected, of which 2 with only CIM. Frs3.1 is the most important QTL with a R 2 = 0.15. Both parental alleles contributed to the shape of the fruit (increasing the ratio Frl/Frd) with 6 alleles from Criollo de Morelos and two from Yolo Wonder. The total phenotypic variation explained by QTLs was 31%.

Pericarp thickness

Eight QTLs were found (4 with IM and CIM, 3 with only IM and 1 with CIM). Pet3.1 and PetLG15.1 were the mostly important with a R 2 = 0.14 and 0,10 respectively. Total phenotypic variation explained by QTLs was 31% and only Yolo Wonder alleles contributed to the trait.

Number of locules

Nine QTLS (6 for both methods, 1 with IM and 2 with CIM) were detected. NloLG25 and NloLG30 were the most important with a R 2 = 0.13 and 0,11 respectively. Only Yolo Wonder alleles increased the number of locules and total variability explained by QTLs was 46%.

Pedicel length

Six QTLs (4 with CIM and IM, 1 with IM and 1 with CIM) were found.

Pel3.1Im and Pel12.1 are the most significant QTLs (R 2 = 0.12 for both QTLs). Both parental alleles contributed to increase the pedicel length (Pel2.1, Pel3.1IM and Pel12.1 for Criollo de Morelos and Pel1.1CIM, Pel4.1 and PelLG42 for Yolo Wonder). Total phenotypic variation explained was equal to 37%.

Flowering earliness

Five QTLs (of which one detected with only CIM) were found and Flw1.1 and Flw2.1 are the most important (R 2 = 0.10). Both parental alleles contributed to increase the trait and total phenotypic variation explained was 15%.

Axis length

Five QTLs (3 in common for IM and CIM and 2 found with IM) were found. AxlLG47.1 is the most important QTL with R 2 = 0.1. Both parental alleles contributed to increase the axis length and total phenotypic variability explained was 42%.

Number of leaves

Four QTLs of which one detected with IM and CIM, 2 with IM and 1 with CIM were found. NleLG47.1 is the one with strongest effect (R 2 = 0.11).

The total phenotypic variation explained was 25% and both parental alleles contributed to increase the trait (Criollo de Morelos for Nle3.1IM, Nle38.1CIm and NleLG45.1IM and Yolo Wonder for NleLG47.1).

Internode length

Three QTLs were detected and Intl2.1 was the most important with R 2 = 0.11. Criollo de Morelos allele increased the trait for Inl2.1 while Yolo Wonder alleles for Inl1.1 and Inl28.1IM. Toal phenotypic variability explained was only 10%.

Internode growth time

Only 2 QTLs were detected (1 with both methods and 1 with IM).

IntLG47.1 was the most significant (R 2 = 0.11). Yolo Wonder allele contributed for Int4.1IM while Criollo de Morelos alleles contributed for IntLG47.1 Total phenotypic variability explained was 7%.

Axis growth speed

Five QTLs (2 with IM and CIM, 3 with CIM) were found. Axs2.1CIM

showed the highest effect with R 2 = 0.1. Total phenotypic variation explained by QTLs is 44%. Criollo de Morelos alleles contributed for Axs2.1CIM, Axs4.1 and Axs9.1 while Yolo Wonder alleles influenced Axs2.2CIM and AxsLG32.

Perennial X Yolo Wonder population

Ten traits were analysed in this progeny, and a total of 28 QTLs (Table 9), ranging from 1 to 5 per trait were identified. No significant digenic interactions were detectable for all the traits in study (P<10 -6 ).

Logarithm of fruit weight

Five QTLs were found, of which 3 detected with both methods and 2 with only IM. Lfw2.1IM, Lfw7.1IM and Lfw11.1IM had the largest effect (R 2 = 0.21, 0.23 and 0.22 respectively) while all detected QTLs detected explain 57% of the total phenotypic variation. For all QTLs, the alleles from variety Yolo Wonder were found to increase fruit weight.

Fruit length A total of 4 QTLs were detected, of which two with CIM method. Frl3.1 was the one with major effect (R 2 = 0.26) while on the whole the QTLs found explained 49% of the total phenotypic variation. Both parental alleles contributed to increase the fruit length i.e.: the Perennial allele for

Frl3.1 and Yolo Wonder alleles for Frl2.1 Frl3.2CIM and Frl11.1CIM.

Fruit diameter

Five QTLs were found for this trait, 3 detected with both methods, and 2 with IM. Frd3.1, Frd7.1IM and Frd2.1 are the ones with most remarkable effects (R 2 = 0.22, 0.19 and 0.18 respectively) while the total phenotypic variability explained by QTLs was 67%. Only the alleles from Yolo

Wonder parent increased the fruit diameter.

Fruit shape

The total phenotypic variation explained by QTLs was 56%, although only 2 QTLs were found with both IM and CIM. Frs3.1 is the most influent (R 2 = 0.64). Only Perennial alleles contributed to the shape of the fruit.

Flowering earliness

Two QTLs (of which one with only CIM) were detected with Flw2.1

showing the greatest effect (R 2 = 0.67). Only Perennial parent's alleles increased the trait value and total phenotypic variation explained was 56%.

Axis length

One QTL was detected with both methods on chromosome 2. The R 2 value is equal to 0.39 % and Perennial allele increased the trait value.

Number of leaves

Three QTLS of which one detected with IM and CIM, and 2 with CIM were found. Nle2.1 is the one with strongest effect (R 2 = 0.37). The total phenotypic variation explained is 49% and both parental alleles contributed to the trait (Perennial for Nle2.1 and Nle5.1CIM, and Yolo Wonder for Nle12.1CIM).

Internode length 2 QTLs were detected and Inl2.2 was the most important with R 2 = 0.23.

Perennial alleles increased the trait valu for both QTLs. Eleven traits were analysed in this progeny and a total of 33 QTLs (Table 10), ranging from 1 to 5 per trait were identified. No significant digenic interactions were detectable for all the traits in study (P<10 -6 ).

Logarithm of fruit weight

Four QTLs were found, all detected with both methods. Lfw11.1, Lfw 11.2 and Lfw2.1 had the largest effect (R 2 = 0.28, 0.26 and 0.24 respectively) and all QTLs detected explain the 47% of the total phenotypic variation. For all QTLs, the alleles from the large fruited accession Vania increased fruit weight.

Fruit length

Five QTLs were detected, of which one with both methods, 3 using CIM and one by IM. Frl9.2 was the one with major effect (R 2 = 0.15) and the total of QTLs found explained the 29% of the total phenotypic variation.

Both parent's allele increased for the length of fruits: the H3 allele for

Frl1.1CIM and Vania alleles for Frl2.1CIM, Frl7.1CIM, Frl9.1CIM and Frl9.2.

Fruit diameter

Five QTLs were found for this trait, 2 detected with both methods, 1 with IM and 2 with CIM. Frd11.1 and Frd2.1IM are the ones with most significant effects (R 2 = 0.26 and 0.22 respectively) while the total phenotypic variability explained by all QTLs was equal to 58%. Only the Vania parental alleles contributed to increase the diameter of fruits.

Fruit shape Four QTLs were detected, of which 2 with CIM. Frs11.1 is the most important QTL with a R 2 = 0.19. Only H3 alleles contributed to increase the ratio of length to width of the fruit and the total phenotypic variation explained by all the QTLs is 48%.

Pedicel length

Four QTLs (3 with CIM and IM and 1 with CIM) were found. Pel8.1 is the most significant (R 2 = 0.27). Both parents contributed to increase the pedicel length (H3 for Pel6.1, Vania for Pel8.1, Pel11.1 and Pel11.2).

Total phenotypic variation explained is equal to 52%.

Flowering earliness

Two QTLs were detected with both methods and Flw2.1 is the one with major effect (R 2 = 0.21). Both parental alleles increased the flowering date and total phenotypic variation explained was 17%

Axis length

Two QTLs were found by CIM and IM. Axl2.1 is the most important QTL with R 2 = 0.36. Only the H3 parent alleles increased the axis length.

Total phenotypic variability explained was 37%.

Number of leaves

Only one QTL was detected with both methods. Nle2.1 has a strong effect (R 2 = 0.47). The total phenotypic variation explained was 47% and the H3 allele contributed to the trait.

Internode length

Two QTLs were detected (one by IM and one by both methods). Inl1.1 was the most important with R 2 = 0.22. H3 alleles increased the internode length at both QTLs and the total phenotypic variability explained was 27%.

Internode growth time

One QTL detected by both CIM and IM was found. Int2.1 has a strong effect with R 2 = 0.51. H3 allele increased the growth speed of the main axis at the QTL detected.

Axis growth speed

Three QTLs were detected with both methods. Axs2.1 was the most significant (R 2 = 0.21). H3 alleles contributed for all the QTLs detected.

Total phenotypic variability explained was 0.43%.

Discussion

Aim of this part of the experimental work was to detect QTLs controlling horticultural traits in the intra-specific genetic linkage map (YC) based on RILs previously developed (see chapter 2), and to validate their position by alignment with other two intra-specific genetic linkage maps (PY and HV) based on DH progenies published by [START_REF] Lefebvre | Towards the saturation of the pepper linkage map by alignment of three intraspecific maps including known-function genes[END_REF]. This will make it possible to obtain more precise and reliable information on the genetics of horticultural traits and identify genomic regions playing a key role in controlling their expression.

General features of the data and QTL detection

Distribution of phenotypic data between the three populations were similar for almost all of the traits. An exception was the distribution of the length of the fruit in the HV population, presumably due to the more elongated shape on the barriers of the parent Vania in comparison with the parent Yolo Wonder.

Correlations within fruit and plant traits were always highly significant.

Correlations between plant and fruit traits were not detected in the YC progeny, but were significant in the PY and HV populations. A possible explanation might be found out in the genetic structure of the latter two populations. Indeed, the DH progenies were originated by a lower number of recombinant events and presumably they might have conserved larger association blocks which were responsible for the detected correlations. Classical quantitative genetics assumes that trait correlation can be attributed to the effect of pleiotropy or to the tight linkage of genes. From the present results it appears that pleiotropy might be the major reason for the observed correlations between plant and fruit traits in PY and HV populations, in which several QTLs responsible for them co-localised in the same genomic regions (i.e. on chromosome P2 and P11). On the contrary, in the YC population few QTLs for plant and fruit traits co-localised, and this might justify the absence of significant correlations. High reproducibility of the data between repeats allowed to estimate the heritability for the traits in study, although phenotypic tests were not performed in different years and environments. The h 2 values were very high for all traits and in all the populations, and comparable to those detected by Ben Chaim et al.

(2001a) but higher than those found by Rao et al. (2003).

Only QTLs detected with IM and/or CIM and above the LOD threshold at p=0.05 were considered. Some major effect QTLs were found in all the populations: i.e. Frl4.1 and Frs3.1 in the YC, Frl3.1, Frs3.1 and Nle2.1 in the PY and Axl2.1 and Int2.1 in the HV. The percentage of genetic variation explained by QTLs was highly variable in relation to the trait and population considered. Fruit diameter always showed the highest R 2 value (from 0.91 in YC to 0.58 in HV). On the contrary the internode lenght and the internode growth time showed, on average, the lowest R 2 values. Moreover, the highest percentage of explained variation was found when few QTLs with high individual R 2 (e.g. fruit shape or flowering earliness in PY population) or many QTLs with minor effects (e.g. fruit diameter in all progenies) were detected. Global R 2 may depend on the accuracy of the linkage map, the between-marker distances and the mapping algorithm used (Jansen et al. 1995). In addition, the genetic structure of the trait, the dimension of the segregating populations [START_REF] Melchinger | Quantitative trait locus (QTL) mapping using different testers and independent population samplex in maize reveals low power of QTL detection and large bias in estimates of QTL effects[END_REF], Utz et al. 2000), genetic background, environment, and interactions among QTL, might bring to an uncomplete QTL detection. Indeed, the high level of heritabilities detected and the incomplete percentage of variation explained by QTLs for all traits in all the progenies, lead to assume that not all QTLs were detected. Moreover the genome coverage of the YC map was about 85% which presumably limited the power of detecting low effect QTLs.

Effect of selective sampling and reduced population size on

QTL detection

An optimised sampling method approach based on the use of MapPop software [START_REF] Brown | MapPop 1.0: Software for selective mapping and bin mapping[END_REF] was applied to evaluate the reliability of QTL analysis in reduced subpopulations of 141 and 93 RILs.

As expected the number of detectable QTLs decreased by reducing population size. Only QTLs with the highest LOD were found for fruit weight and receptivity. For axis length, none of the previously spotted QTLs was identified in the sub-populations but a new one was identified on chromosome P12 in the population of 93 RILs. The only explication for that seems to be an error due to the reduced number of individuals assayed. The R 2 for each trait was checked in the 2 sub-populations and decreased with the decrease in the number of individuals tested. On the basis of the results previously reported (see chapter 2) selective genotyping is suitable for the identification of new markers to be added in a previously developed genetic map. On the contrary, the selective genotyping approach seems not appropriate for QTL detection.

Genetic architecture of the QTLs of the different traits v. Allelic diversity, cluster organization and conservation of QTLs in pepper germplasm

Most of the chromosomes were involved in the genetic control of at least one of the 13 traits analysed, and the organization of QTLs in clusters explains the correlations found between traits.

QTLs controlling fruit traits were mainly concentrated on P2, P3, P10

and P11 in all the progenies, together with progeny specific clusters on P4 and P12 for YC. Clusters of QTLs for fruit traits on P2, P3, P4, P10

were previously detected in intra as well as inter-specific crosses with major effects on P3 (Ben Chaim et al. 2001a, Rao et al. 2003). A new cluster on P11 with major effects on fruit weight and diameter was detected in our 3 populations. The same cluster with minor effects was also detected in the inter-specific cross by Rao et al. (2003).

The comparative analysis of QTLs in the intra-specific pepper populations showed coherence in the results, thus allowing QTLs positions in the pepper genome to be confirmed.

In the three populations (Table 12) alleles from both parents were found to contribute for fruit length and pedicel length.

Major effect QTLs controlling fruit traits were found to co-localize on chromosome P2 for fruit diameter, on chromosomes P3 for fruit shape and fruit diameter and on chromosome P11 for fruit diameter. The P2, P3 and P11 alleles increasing the fruit diameter all originated from large the fruited parents, while the P3 and P10 alleles controlling the fruit shape always derived from the small fruited ones. Selection for elongated shape may require to select for the alleles of small fruited varieties at major QTLs in chromosome P3 and P10, but length of the fruits can be increased in selecting alleles from large fruited varieties at QTLs in Chromosomes P2, P4, P7 and P11.

Concerning plant traits, major effect QTLs were always found to cluster on P2 for flowering date, axis length and number of leaves, thus showing a tight co-localization. The P2 alleles increasing the axis length, the flowering earliness and the number of leaves originated from small fruited parents while those increasing the axis speed growth from large fruited ones. Those traits (including the calculated parameters Axs, Inl, Int) were presumably under a common genetic control (pleiotropy) due to their high level of co-localization and correlation.

By considering both plant and fruit traits, putative pleitropic control was detected on chromosome P2. QTLs for fruit weight, fruit length and internode growth time are influenced by large fruited parent alleles in the HV and PY populations; in addition the fruit diameter appeared controlled by large fruited parents in all the three progenies. Vice versa flowering earliness, axis length, internode length and axis growth speed were always controlled by small fruited parent. These results show that, as previously observed in tomato [START_REF] Bernacchi | Advanced backcross QTL analysis in tomato. I. Identification of QTLs for traits of agronomic importance from Lycopersicon hirsutum[END_REF], chromosome P2 and T2 deeply influence the fruit size in both species.

The QTLs in common between the two or three populations analysed are listed in table 13. Plant traits are in general controlled by both parental alleles in the YC population, while in the PY and HV populations only two (number of leaves, internode growth time) and one (flowering earliness) traits respectively are controlled by both parental alleles, despite the presence of transgressive individuals for many traits. These results presumably might be explain by the presence of undetected QTLs.

QTLs analysis revealed the presence for the YC, PY and HV populations of several QTLs on chromosome P2. In PY and HV these QTLs are located in the top part of the chromosome while, in the YC they are located in the middle part of chromosome P2. A possible explanations is the presence in the top part of the chromosome of more common mapped markers in two DH populations.

Transgressive segregation occurred for several traits. in particular for plant traits. Several authors (DeVicente and Tanksley, 1993, Rieseberg et al. 1999, Rieseberg et al. 2003) pointed out that transgressive segregation might result from the appearance of combinations of alleles from both parents that have effect on the same direction. Moreover.

DeVicente and Tanksley (1993) stated that the more similar the phenotype of the parents is, the more likely that transgressive individuals would occur, as we observed for pedicel length and the number of leaves in the YC population, for flowering earliness, axis length, internode length internode growth time and axis growth speed in the PY population and for flowering earliness and internode length in the HV population. To confirmation of that, in the YC population no transgressive segregation was observed for the traits affected by only Yolo Wonder alleles as no one of the YC individual presented a phenotypic value similar to large fruited parent. On the contrary in the PY population, trasgressive segregation was observed for traits influenced by Perennial alleles, while in the HV population trasgressive genotypes were found for traits controlled by only Vania (Internode length). Presumably this was a consequence of the only partial identification of the QTLs involved in the genetics of the character. In order to evaluate the goodness of QTL analysis, a trait influenced by alleles from both Yolo Wonder and Criollo de Morelos: i.e. the pedicel length was analysed (Figure 5). The genotypes of the 3 individuals with the highest (A, B, C) and lowest (C, D, E) trait value was assayed using the graphical genotypes approach [START_REF] Young | Restriction fragment length polymorphism maps and the concept of graphical genotypes[END_REF]. Alleles from Yolo Wonder were found to increase the trait value for QTLs placed on chromosome P1, P4 and LG42; Criollo de Morelos 334 alleles positively influence the trait for QTLs located on chromosome P2, P3 and P12. For the individuals with the highest value, it was found out that their genotype contained all the six alleles increasing the trait value, with the exclusion of the individual B, whose genotype presents the opposite allele on chromosome P12. On the contrary, the individuals with shorter pedicel length contained no one of the alleles responsible for increasing the trait value, with the exclusion of individual D for the QTL located on chromosome P2.

By applying multiallelic breeding programs, favourable allelic combinations may deliver transgressive genotypes which could be exploited for the genetic improvement of important agronomic traits. Many minor QTls controlling number of locules were identified in the YC populations, a result in contrast with those reported in tomato [START_REF] Lippman | Dissecting the genetic pathway to extreme fruit size in tomato using a cross between the smallfruited wild species L. pimpinellifolium and L. esculentum, var. Giant Heirloom[END_REF] where one major QTL on T11 and 2 minor QTLs on T2 controlling this trait were found. Pel4.1 Two QTLs controlling the flowering earliness detected by Frary et al. (2003) in eggplant and by [START_REF] Vicente | QTL analysis of transgressive segregation in an interspeciÞc tomato cross[END_REF] and Grandillo and Tanksley (1996) in tomato (Fw1.1 and Fw2.1) were also detected in our work, one in the YC progeny (Flw1.1, which was already found by Rao et al. 2003) and one shared by the three populations (Flw2.1), allowing the localisation of important genomic regions affecting the earliness of plants flowering on chromosome P1 and P2. For the primary stem height, a major QTL was always found on chromosome P2. A putative orthologous QTL was also detected by [START_REF] Paran | QTL analysis of morphological traits in a tomato recombinant inbred line population[END_REF] on tomato and in eggplant by Frary et al. (2003). Results showed that some domesticated-related traits, as the fruit weight and the fruit shape have been conserved during the evolution and the domestication in the Solanaceae family. Notwithstanding, when exploring synteny, orthologous QTLs show differences in effect between species, such as the fs10.1/ovs4.1 which is the major effect QTL in tomato and eggplant but not in pepper. The main goal of the present PhD thesis was to integrate genetic information for horticultural traits and disease resistances on a single high resolution linkage map and to generate new tools for further improvements of pepper genome in multitrait breeding programs.

Conclusions

Conclusion of the experimental work

The experimental activities carried out can be summarized as follows:

• to develop new EST derived SSR markers, to be used for genetic mapping and phylogenetic studies.

• to construct a new high resolution genetic linkage map based on 297 RILs obtained from the cross 'Yolo Wonder' x 'Criollo de Morelos 334' (CM334) and to evaluate the efficiency of mapping and QTL detection in selected subsets of the RIL population.

• to use the newly developed map for identifying QTLs controlling horticultural traits, and compare their position between pepper varieties.

• to analyse macro-synteny among Solanaceae species by comparing the position of QTLs for horticultural traits in pepper, tomato, potato and eggplant.

Development of new SSRs and pepper map improvement

On the whole, 204 pepper EST-derived SSRs were developed and 49 were found to be polymorphic among the parents of the present and/or previously developed pepper maps. Forty-seven SSRs were found polymorphic between the accessions 'Tabasco' and 'P4' [START_REF] Sasvári | Construction of a new inter-specific genetic map in pepper based on AFLP and microsatellite markers[END_REF]), while 21 were successfully mapped in the intra-specific population developed in this study.

The number of alleles detected per SSR marker varied from 2 to 9 (mean 4.5). The largest variation in amplicon size (261-349bp) was present at EPMS-923. The PIC value of each of the 49 mappable markers ranged from 0.24 to 0.86 (mean 0.62 ± 0.02). EPMS-650 had the highest PIC, and EPMS-603 and EPMS-670 the lowest.

The EST-derived SSR markers were also investigated for their usefulness in diversity analyses by assessing genetic similarity (GS)

among 16 test genotypes from eight Capsicum species. Results showed that GS varied from 0.09 ('Tabasco' vs. 'CM334') to 0.81 ('Chi1' vs. 'Chi7'). Genetic relationships between the accessions was in good agreement with known taxonomic classifications and with those previously generated by applying RFLP, RAPD and AFLP markers (Prince et al. 1994;Rodriguez et al. 1999;[START_REF] Portis | Multivariate analysis of genetic relationships between Italian pepper landraces[END_REF] [START_REF] Scott | Analysis of SSRs derived from grape ESTs[END_REF]. Some authors pointed out that certain microsatellite PCR primer pairs designed for one organism may not be applicable across genera, because of high variation in flanking sequences of microsatellites between the donor and the receptor, and the frequent loss of the microsatellite motif where amplification occurs [START_REF] Smulders | Use of short microsatellites from database sequences to generate polymorphism among Lycopersicon esculentum cultivars and accessions of other Lycopersicon species[END_REF] (2002). Unfortunately, QTLs comparison among pepper tomato and eggplant was hampered by the limited number of shared markers between these genera, and particularly between our map and the tomato, potato and eggplant maps, preventing any conclusion toward orthology. A further constrain was due to the low number of common horticultural traits analysed, which limited the identification of the chromosomic regions involved in traits control. On the whole, QTL analyses performed using three different intra-specific progenies allowed a more precise localisation of the genomic regions involved in the control of important key traits, such as fruit weight, fruit diameter and fruit shape.

A further activity carried out in the present PhD thesis was to identify sub-samples of individuals suitable for both mapping and QTL analyses. This was achieved by applying the MapPop software from [START_REF] Brown | MapPop 1.0: Software for selective mapping and bin mapping[END_REF]. Four subpopulations of 141, 93, 45 or 29

individuals were identified and their potential for mapping was tested.

Results showed that larger subpopulations delivered reasonable mapping precision, which as expected was higher when the largest subpopulation was genotyped. Moreover when the attention was focused on the minimum subset of individuals which allowed to assigned a new marker to a linkage group, the 45 individual subpopulation made it possible to obtain reliable results. The quality of QTL detection was assayed on three traits, by comparing the results obtained in the RIL population of 297 individuals as well as in the subpopulations of 141 and 93 individuals. This approach was useful for traits controlled by major

QTLs with an R 2 value >30-40%. On the contrary, the QTLs with weak effect controlling plant height were detectable only in the whole population. This clearly shows that polygenic traits governed by multiple genes with weak effects require large mapping populations for exhaustive genetic analyses.

The results here reported open new questions, and suggest to prosecute experimental work as reported below.

Map improvement

The map developed during the PhD thesis will require further improvement. The saturation of the YC map but also a better anchorage with the previously developed pepper maps are needed.

Several linkage groups still remain unassigned, thus further markers has to be applied for the detection of bridge markers which will help to merge these unlinked LGs and to attribute them to chromosomes. AFLP markers represent an useful tool as they generate many polymorphic fragments per primer combination, thus increasing the probability of detecting useful bridge markers. However a limiting factor is due to their trend to cluster and not uniform distribution in the genome. Suitable New markers might be selected by using the subpopulation of 45 individuals identified by applying the MapPop software [START_REF] Brown | MapPop 1.0: Software for selective mapping and bin mapping[END_REF] thus reducing time and costs for future genotyping.

In addition a new integrated map will be developed by merging the three intra-specific maps developed (YC, HV and PY). The new integrated map could bring to an improvement in the QTL analysis, allowing to better detect QTLs position on chromosomes.

2.2 Widen the knowledge of the genetic basis controlling horticultural traits and pathogen resistance .

The QTL analyses performed on 13 horticultural traits contributed to a better understanding of pepper genome organization. New horticultural traits related to plant architecture and development has been analysed. The integration of these new information with those related to the genetic determinism of resistance to pepper diseases will make it possible to better identify useful markers and suitable strategies for future application of breeding programs based on Marker Assisted Selection (MAS). Information at present available on genes and QTLs for horticultural and disease resistance traits highlight the following:

-In chromosome P1, P2, P3, P4, P10, P11 and P12 linkages between fruit traits, plant traits and disease resistance traits have been identified (Figure 1). The -In chromosome P9 the imprecise location of Me (nematode resistance) genes needs further linkage analysis to better target the relative location of Me-genes cluster and horticultural trait QTLs.

To better precise QTLs location, gene candidate approach and synteny among species will be used. In particular the genetic information from

Arabidopsis thaliana and other plant species will be used to generate markers located near putative genes of interest which might be mapped.

Towards the MAS (Marker Assisted Selection)

Breeding programs based on MAS strategies represent the applicative extension after the high resolution mapping and QTL analyses performed in this study. Previous experience in MAS selection for polygenic traits demonstrated that MAS is effective in selecting the targeted QTLs (foreground selection) and accelerating the recovering of the expected genetic background (background selection) [START_REF] Hospital | Marker-assisted introgression of quantitative trait loci[END_REF]. However, unfavourable genetic linkages may hamper the side by side progress for both horticultural and resistance traits (Thabuis et al 2004 a and b).

Selection for multiple traits requires first of all to cross parental lines (biparental or multiparental crosses) with the goal of including the totality of favourable alleles (Ribaut and Betran, 1999) and to select the expected recombinant individuals in the progenies. The selection of large fruited cultivars resistant to pathogens will depends on the genetic structure of chromosomes carrying QTLs. In the RILs population developed, chromosomes P4, P5, P6, P10, P11, P12 show that P.

Capsici resistant alleles are conserved between parental lines together with plant and/or fruit traits QTLs.

On the other hand, in chromosome P9, the nematode resistance genes are linked in repulsion to fruit traits QTLs.

Graphical genotype of the RIL individuals will have to be examined to select individuals with interesting recombinations which will be used as parental lines of future breeding programs.

By using the multiparental approach, markers have to be evaluate for their polymorhism and some markers may have to be converted from RFLP or AFLP into SCARs, STSs, SNPs to obtain reliable and codominant markers which are less time-consuming and less costly to assay. These markers might also be transferable to related species, thus increasing the possibility of detecting important genomic regions controlling for traits of interest of Solanaceae species.

Towards the MAS (Marker Assisted<Selection) References

The objective of the present PhD thesis was to develop a high resolution intra-specific map of pepper (C. annuum L.) in order to integrate genetic information for horticultural traits and to generate new tools for further improvements of pepper genome in multitrait breeding programs.

At first 49 EST derived SSR markers were developed for mapping purposes, and for providing anchor markers in crossspecies comparative mapping.

The high resolution intra-specific map was constructed using a population of 297 F5 recombinant inbred lines. The parents were the large-fruited inbred cultivar 'Yolo Wonder' and the hot pepper line 'Criollo de Morelos 334'. A total of 597 molecular markers were applied. The framework map covered 1857 cM with an average inter-marker distance of 5.71 cM. In addition the use of the largest population ever used in pepper and he use of an F5 generation provided a good level of resolution.

A QTL analysis of 13 horticultural traits (i.e fruit and plant traits) was performed in the RIL mapping population as well as in two double haploid populations originating from the crosses Perennial X Yolo Wonder and H3 X Vania. A total of 14 and 6 common QTLs controlling fruit and plant traits respectively were found to be shared among the three populations.

An analysis of synteny among tomato, pepper, potato and eggplant for common genomic regions controlling horticultural traits was carried out. Putative orthologous regions were found, which may have been conserved during evolution and independent selection performed on these species.

Through selective genotyping subsets of the most informative RILs (141, 93, 45 or 29) were identified, in order to reduce the genotyping and phenotyping efforts. Results showed that larger subpopulations delivered reasonable mapping precision. On the contrary, the selective genotyping approach for QTL detection seems not appropriate because only major QTLs with an R 2 value >30-40% were detected in the RIL subsets.

Figure. 1

 1 Figure.1 Phenotyphic variation in fruits of different Capsicum species. Sample of the INRA-Avignon pepper germplasm (picture from Alain Palloix).

Figure 2 :

 2 Figure 2: CMV symptoms on leaves and fruits (INRA).

Figure 3 :

 3 Figure 3: TMV symptoms on plant and fruits (INRA)

Figure 4 :

 4 Figure 4: PVY leaf mosaic and vein necrosis (INRA)

Figure 5 :

 5 Figure 5: discoloration of fruits due to TSWV (INRA)

Figure 6 :

 6 Figure 6: Collar necrosis and wilt symptoms along irrigation furrows due to Phytophthora capsici; (INRA)

Figure 7 :

 7 Figure 7: Defoliation and white sporulations on leaves caused by Leveillula taurica; (INRA)

Figure 9 :

 9 Figure 9: wilt symptoms and necrosis of vascular tissue of the primary stem due to Ralstonia solanacearum. (INRA)

Figure 10 :

 10 Figure 10: Caryotype of most Capsicum species including most wild C. annuum and all C. chinense and C. frutescens (above); caryotype specific to all domesticated and a few wild C. annuum (middle); possible variations in the location and number of chromosome satellites (1 to 3) in the genus (below). (From C. Djian Caporalino et al 2006)

  demonstrated that inter-specific progenies exhibited end-chromosomes exchanges. At least 2 chromosome pairs are concerned by such exchanges between cultivated C. annuum and C. chinense which were used in mapping.

Figure 11 :

 11 Figure 11: Inter-specific map by Livingstone et al. (1999) and its alignment with the tomato map.

  Pvr4 and Pvr7 for resistance to potyviruses, the Tsw for resistance to TSWV (Grube et al. 2000a), the QTL Pc_10.1 for resistance to Phytophthora capsici and the QTL Lt_10.1 for the resistance to Leveillula taurica was identified (Figure12). Several studies compared the resistance loci detected in pepper with those detected in tomato and potato. An overall genome comparison was published by Grube et al (2000b) giving evidence for map collocation and synteny of position between the 3 species. Concerning disease resistance, no general rule can be established for functional synteny within the family. For example, the pepper orthologs of tomato Sw and Tm-2 genes already exist in pepper, but resistance to the same pathogens (TSWV and ToMV) is controlled by distinct genes in pepper. Conversely, a few studies delivered expectation for orthology between genes conferring resistance to the same pathogens in the different host species. The Me3 and Me4 locus mapped on pepper chromosome P9 are colinear to the tomato Mi-3 on chromosome T12 and the potato Gpa2 on chromosome XII (Djian-Caporalino et al. 2001). The major resistance pepper QTL to Phytophthora capsici on the chromosome P5

  Rao et al. (2003), using an inter-specific C. annuum x C. frutescens cross, analysed 10 different traits including fruit weight, fruit shape and flowering earliness.Analyses on horticultural traits in pepper were mainly focused on fruit traits, thus no information are at present available on QTLs controlling plant traits other than plant height(Ben Chaim et al. 2001a) and flowering time (Rao et al. 2003). Ben Chiam et al. (2001) revealed a total of 55 QTLs, most of them clustered on chromosomes P2, P3, P4, P8 and P10. In the study performed by Rao et al. (2003), a total of 56 QTLs were identified and the majority of them clustered on chromosomes P1, P2, P3, P4, P8, P10 and P11. These results underline the involvement of these chromosomes in horticultural traits control. Moreover some QTLs detected, in particular for fruit diameter and fruit weight, were closely correlated, as result of the high genetic linkage present among these traits. Several putative orthologous QTLs were identified in pepper. In his work, Rao et al. (2003) stated that 10 QTLs detected could be orthologous with those previously described by Ben Chaim et al. (2001a). These included 3 QTLs for fruit weight (fw2.1, fw3.1 and fw4.1), fl2.1 for fruit length and the major effect QTL on chromosome 3 controlling fruit shape which seems to be conserved in intra-specific crosses and in crosses of C. annuum with C. chinense and C. frutescens

Figure12:

  Figure12: Genetic map of pepper with localization of major genes and major QTLs for disease resistance and horticultural traits (from Djian-Caporalino et al., 2006). Only the major genes and the major QTLs (those with the highest R2 value for each trait) were positioned. Major QTLs are indicated in rectangular boxes. Abbreviations for QTLs: cap= capsaicin content, fd=fruit diameter, fl=fruit length, fs=fruit shape (ration length/width), pd=pedicel diameter, pl=pedicel length, cmv=resistance to CMV, Phy=resistance to P. capsici, Lev=resistance to L. taurica.

  variable when considering the large diversity of both local and internationally commercialized cultivars. Large breeding efforts have also been performed concerning plant traits, as plant height, determinate/indeterminate growth, flowering earliness and plant architecture, because those traits determine the plant adaptation to the agro-climatic environment, and to the cultivation system (open field/protected, fresh market/industry). Breeding for chemical composition is generally focused on high carotenoid content of mature fruit for paprika powder and oleoresin production (food staining). Specific cultivars have been bred with up to 50 times the capsantin/capsorubin content of fresh market cultivars (Hurtado-Hernandez and Smith 1985) Pungency is another key trait governed by the major gene C and by quantitative factors that control the composition and the content in the different capsaicinoids.

  varieties. Monogenic resistance to TMV, ToMV and PMMV conferred by the dominant allele at the L locus was introduced in most of the present cultivars, as the resistance to PVY, TEV and nematodes that also depends on major resistance genes. Because virulent variants of these viral and nematode pathogens were present in the field, new genes or alleles were characterized in genetic resources and progressively introduced in cultivars. No major resistance genes were available against major fungal or oomycete diseases like powdery mildew (due to L. taurica), anthracnose (due to Colletotrichum spp), and Phytophthora root rot, nor against one major virus disease of pepper due to CMV. In those cases, breeders exploited the quantitative resistance components from different accessions. The breeding programs were rather successful with CMV resistance, delivering cultivars with a partial resistance fitting the different cultivation areas. Considering

In

  Fig. 1 UPGMA dendrogram of the 16 genotype set, based on 219EST-SSR alleles. Sample codes are described in Table1.

  AFLPs, 40 SSRs, 19 RFLPs, 17 SSAPs and four STSs).Of these, 489 (428 AFLPs, 25 SSRs, 16 RFLPs, 16 SSAPs and four STSs) were distributed on 49 LGs at a LOD of 8 and a maximum r value of 0.1. Of the LGs, 14 were composed of at least 10 (and up to 60) markers, and 35 carried less than 10 markers. The framework map (Figure2) used 323 markers (about 55% of the total markers) whose order could be confirmed with a LOD of 3. It covers 1857cM, with an inter-marker distance of 5.71 ± 5.70 cM. Based on previously published maps[START_REF] Lefebvre | Towards the saturation of the pepper linkage map by alignment of three intraspecific maps including known-function genes[END_REF] Paran et al. 2004), 45 markers (32 AFLPs, 12 RFLPs and one STS) allowed for the assignment of 23 LGs to chromosomes. Thus 23

  1553 cM, leaving 26 LGs (304 cM) non-assigned. About 77% (i.e.. 250) of the framework map markers were assigned to pepper chromosomes (223 AFLPs, 10 SSRs, 14 RFLPs, two SSAPs and one STS) which were separated by a mean of 6.54 ± 6.08 cM. Chromosomes P1, P2, P3, P4, P5, P8 and P9 were composed of two or three merged LGs, with the most likely arrangement (LOD>3) shown on Figure 2. Chromosomes P4, P10, and P11 comprised two unmergable LGs. LG23 could not be assigned to chromosome P9, despite carrying the Scar_CD STS locus, which has been recently located on P9 (Djian-Caporalino et al. unpublished) since its location at one or the other extremity of the chromosome was uncertain. The genetic length of the chromosomes with merged LGs (P1, P2, P3, P4, P5, P8 and P9) ranged from 74.8 cM (P6) to 205 cM (P5 and P9).

(

  2002) and[START_REF] Paran | An integrated genetic linkage map in pepper (Capsicum spp.)[END_REF]. Based on 32 shared markers,23 LGs could be aligned with regions on the pre-existing maps. All common AFLP markers mapped to the same location, establishing their locusspecificity (Rouppe van derVoort et al. 1997;[START_REF] Lefebvre | Towards the saturation of the pepper linkage map by alignment of three intraspecific maps including known-function genes[END_REF]. The alignment was successful for all the chromosomes except P1 and P8.Chromosome P1 of the integrated map was split into two LGs in both the present map, and that of[START_REF] Lefebvre | Towards the saturation of the pepper linkage map by alignment of three intraspecific maps including known-function genes[END_REF]. P1 is colinear with the upper part, and P8 colinear with the lower part of the integrated LG1.Chromosome P8 of the integrated map aligns with the intraspecific chromosome P1 of[START_REF] Lefebvre | Towards the saturation of the pepper linkage map by alignment of three intraspecific maps including known-function genes[END_REF], although it has not been possible to make an alignment with any of the present LGs due to a lack of shared markers. These results confirm the suggestion, made by[START_REF] Pickersgill | Cytogenetics and evolution of Capsicum L[END_REF], of a reciprocal chromosomal translocation between annuum and chinense, which could be responsible for pseudolinkage between loci close to the interchange breakpoint. This breakpoint might be localised at 75 cM of LG1 of the integrated map ofParan et al.

  markers Figure1. Proportion of skewed markers in the three classes (i-markers included in the framework map, iimarkers assigned to LGs and placed with the Mapmaker command "try" and iii-unlinked markers)

Figure 2 .

 2 Figure 2. Framework map consisting of 323 markers, obtained from the F5YC RIL mapping population. In normal bold, markers used as anchors to assign LGs to chromosomes. Markers on the right of the chromosomes are unordered but placed by the "try" command. In Italic and bold, SSR markers. # indicates markers showing segregation distortion at P<0.01 in the framework map. Chromosome orientation follows LEFEBVRE et al. (2002).

  13 horticultural traits (i.e fruit and plant traits) was performed on 3 intra-specific populations of pepper (C. annuum) originating from the crosses: Yolo Wonder X Criollo de Morelos (YC), Perennial X Yolo Wonder (PY) and H3 X Vania (HV). A TOTAL OF 78, 24 AND 30 QTLS WERE DETECTED FOR THE YC, PY AND HV POPULATIONS RESPECTIVELY WITH A P LEVEL OF 0.05 AS THE THRESHOLD TO DECLARE THE PRESENCE OF A QTL. QTL comparison among the three populations revealed that 9 QTLs were located in the same genomic regions, while 11 were detected in only two of the three populations considered, i.e. 3 in YC and PY populations, 4 in PY and HV and 4 in YC and HV. AN ANALYSIS OF SYNTENY AMONG TOMATO, PEPPER, POTATO AND EGGPLANT FOR COMMON GENOMIC REGIONS CONTROLLING HORTICULTURAL TRAITS WAS CARRIED OUT. PUTATIVE ORTHOLOGOUS REGIONS WERE FOUND, IN PARTICULAR FOR FRUIT WEIGHT, FRUIT LENGTH, FRUIT DIAMETER, FRUIT SHAPE, FLOWERING EARLINESS AND PLANT HEIGHT, WHICH MAY HAVE BEEN CONSERVED DURING EVOLUTION AND INDEPENDENT SELECTION PERFORMED ON THESE SPECIES Through selective genotyping, by means of MapPop application, subsets of 141 and 93 individuals of the YC population were identified, as being the most informative for future mapping studies and phenotypic tests. The subsets were tested for QTL mapping accuracy of two horticultural and one resistance traits. As expected the number of QTLs detected decreased with the reduction of population size, anyhow, selective genotyping leads to more informative results than the use of random samples. Introduction Pepper, like most cultivated crops, is subjected to intense breeding efforts by Institutes and private companies around the world. Breeders have to combine favourable alleles controlling climatic adaptation, plant architecture, fruit characteristics and disease resistance in each cultivar. This multitrait selection may benefit from favourable linkage between alleles, but unfortunately is often slow down by unfavourable linkages. In pepper, disease resistances are generally introduced from small fruited and pungent local populations into genetically distant elite genitors; moreover, cultivar types strongly differ in plant ideotypes and fruit shapes. This double constraint "multiple ideotypes and exotic germplasm resources" motivates an integrated analysis of traits conferring horticultural characteristics and disease resistance in order to identify possible barriers (unfavourable linkages) to genotype construction. Previous studies report on QTL identification of fruit-related traits in intraspecific (Ben Chaim et al. 2001) and inter-specific crosses (Rao et al. 2003, Zygier et al. 2005); while a few information are available on QTLs controlling plant height (Ben Chaim et al. 2001a) and flowering time (Rao et al. 2003)Comparative genome analysis was carried out in Solanaceae; synteny relationships were explored by using tomato-derived probes in the four most important species: pepper, tomato, potato and eggplant[START_REF] Tanksley | High density molecular linkage maps of the tomato and potato genomes[END_REF][START_REF] Livingstone | Genome mapping in capsicum and the evolution of genome structure in the Solanaceae[END_REF][START_REF] Djian-Caporalino | Root-knot nematode (Meloidogyne spp.) resistance genes Me in pepper (Capsicum annuum L.) are clustered on the P9 chromosome Submitted[END_REF]. Accurate studies on conserved regions affecting pest resistance genes were performed byGrube et al (2000b). Syntenic studies on horticultural traits were done by comparing pepper and tomato(Ben Chaim et al. 2001a, Rao et al. 2003) and, more recently, by comparing pepper, tomato and eggplant[START_REF] Djian-Caporalino | Root-knot nematode (Meloidogyne spp.) resistance genes Me in pepper (Capsicum annuum L.) are clustered on the P9 chromosome Submitted[END_REF], Frary et al. 2003) allowing to better elucidate the genomic organization of Solanaceae . Results showed that some domestication-related traits, like fruit weight and the fruit shape, have been conserved during the evolution and the domestication within the Solanaceae family. Notwithstanding, orthologous QTLs show differences in effect between species.

Figure 2 :

 2 Figure2: Frequency distribution for the 13 traits analysed in the YC population: logarithm of the mean fruit weight value (Lfw), the fruit length (Frl), the fruit diameter (Frd), the fruit shape (Frs), the pericarp thickness (Pet), the number of fruit locules (Nlo), the pedicel length (Pel), the flowering earliness(flw), Axis length (Axl), the number of leaves (Nle), the mean internode length (Inl), the mean internode growth time (Int) , the axis growth speed (Axs). Parental mean values are designated CM334 (Criolo de Morelos), YW (Yolo Wonder) while F1 indicates the hybrid mean.

Figure 3 :

 3 Figure3: Frequency distribution for the 10 traits analysed in the PY population: logarithm of the mean fruit weight value (Lfw), the fruit length (Frl), the fruit diameter (Frd), the fruit shape (Frs), the flowering earliness(flw), Axis length (Axl), the number of leaves (Nle), the mean internode length (Inl), the mean internode growth time (Int) , the axis growth speed (Axs). Parental mean values are designated Perennial (Perennial), YW (Yolo Wonder) while F1 indicates the hybrid mean.

  Means and heritabilities of quantitative traits in the HV population for the parental, F1 and DH generations.

  Potential orthologous QTLs with other solanaceae speciesSeveral QTLs analyses concerning horticultural traits in Solanaceae species are available, including pepper (BenChaim et al. 2001a, Rao et al. 2003), tomato[START_REF] Bernacchi | Advanced backcross QTL analysis in tomato. I. Identification of QTLs for traits of agronomic importance from Lycopersicon hirsutum[END_REF], Grandillo et al. 1999[START_REF] Djian-Caporalino | Root-knot nematode (Meloidogyne spp.) resistance genes Me in pepper (Capsicum annuum L.) are clustered on the P9 chromosome Submitted[END_REF]), eggplant (Doganlar et al. 2002, Frary et al. 2003) and potato(Van Eck et al. 1994).In eggplant[START_REF] Djian-Caporalino | Root-knot nematode (Meloidogyne spp.) resistance genes Me in pepper (Capsicum annuum L.) are clustered on the P9 chromosome Submitted[END_REF] performed analyses on 16 horticultural traits related to domestication.Frary et al. (2003) focused their attention on 18 traits affecting leaf, flower, fruit and plant characteristics.By comparing pepper and eggplant QTLs analysis, some putative orthologous regions have been found. For fruit diameter, Doganlar et al. (2002) detected a QTL on chromosome E11 whose position, by alignment with the integrated map of pepper (Paran et al. 2004) and the comparison between pepper and tomato performed by Livingstone et al. (1999), allow the identification of a putative orthologous QTL in pepper: i.e. Frd12.1. The fruit weight QTL Fw2.1 identified in eggplant by Doganlar et al. (2002), in pepper by Ben Chaim et al. (2001a) Rao et al. (2003) and Zygier et al. (2005) and in tomato by Grandillo et al. (1999), could be putative orthologous to Lfw2.1 detected in two of the three population analysed in this work. The fruit weight QTL Fw11.1 detected by Grandillo et al. (1999), Doganlar et al. (2002) and Rao et al. (2003) was identified in all of the three pepper populations considered on chromosome P11. Frl 2.1 detected in the PY and HV population could correspond to the Fl2.1 QTL detected by Rao et al. (2003) and to tomato fruit length QTL on chromosome T2 (Lippman and Tanksley 2001). Moreover the QTL Frd4.1 seems to correspond to the Fl4.1 QTL detected by Rao et al.(2003) and to the tomato QTL controlling fruit diameter on chromosome T4 (Lippman and Tanksley 2001). The QTL Frs3.1 identified in pepper by Ben Chaim et al. (2001) and Rao et al. (2003) and in tomato by Bernacchi et al. (1998), and Fs10.1 identified in pepper by Ben Chaim et al. (2001) and in tomato by Grandillo et al. (1999) could correspond respectively to Frs3.1 and toFrs10.1 detected in the pepper populations in study. On the contrary, the major ovary shape QTL in eggplant is located on chromosome E4[START_REF] Djian-Caporalino | Root-knot nematode (Meloidogyne spp.) resistance genes Me in pepper (Capsicum annuum L.) are clustered on the P9 chromosome Submitted[END_REF]. At last the Fs10.1 found in pepper seems to be orthologous to Ro gene controlling the tuber shape in potato(Ben Chaim et al. 2003).

Figure 5 :

 5 Figure 5: chromosomes and the LG42 containing QTLs for the pedicel length trait. The colour black in the chromosomes shows the presence of genomic material from the parent CM334 while the white shows the genome from Yolo Wonder. The letter A, B and C indicate the three individuals with the highest transgressive value for the trait, while D, E and F indicate individuals with the lowest phenotypic value. The graphic below the chromosomes represents the phenotypic value of the six most transgressive individuals.

  QTL analyses performed using three different intra-specific progenies allowed to more precisely localise and confirm the genomic regions involved in the control of important key traits, such as fruit weight, fruit diameter or fruit shape. The results presented in this chapter show that 35 of the 78 QTLs detected in the YC population and influencing the 13 horticultural traits analysed were found to control the same trait and were located on the same chromosome in the 3 pepper intra-specific maps. Unfortunately, QTLs comparison among pepper tomato and eggplant was limited by the low number of common horticultural traits analysed, and by the limitation in genome alignment due to the lack

11HVFigure 6 :

 6 Figure 6: Synthesis of the QTLs detected for all traits in the 3 progenies. Detected QTLs and their position on each chromosome and LG is shown. The length of the vertical bars represent the confidence interval of the QTLs defined as the LODmax -1 interval .Traits are indicated with three letters as follows: Logarithm of fruit weight (Lfw), Fruit length (Frl), Fruit diameter (Frd), Fruit shape (Frs), Pericarp thickness (Pet), Number of locules (Nlo), Pedicel length (Pel))Flowering earliness(Flw), Axis length (Axl), Number of leaves (Nle), Internode length (Int), Internode growth time (Int), Axis growth speed (Axs).

  the present study genomic regions controlling both fruit and plant traits were analysed in 3 distinct crosses involving 5 parental lines, which were previously used for the analysis of multiple disease resistance. The 78 QTLs detected in the Yolo Wonder x CM334 population were compared with those identified in two other populations PY (Perennial x Yolo Wonder) and HV (H3 x Vanai). Most of the QTLs were shown to be clustered on chromosomes P2, P3, P10 and P11 for fruit traits, and P2 for plant traits. These QTL clusters were shared among the 3 progenies. Previous analyses in intraspecific and interspecific pepper progenies also delivered clusters of QTLs for fruit traits on the same chromosomes (BenChaim et al. 2001; Rao et al. 2003[START_REF] Zygier | QTLs mapping for fruit size and shape in chromosomes 2 and 4 in pepper and a comparison of the pepper QTL map with that of tomato[END_REF], indicating a large conservation of allele position within the Capsicum genus. On the other hand, parent-specific QTLs were also detected in other chromosomes for fruit as well as plant traits indicating that diversity is available within the C. annuum species and that distinct alleles can be exploited in different crosses.Several common QTLs were found to be shared among the three populations. By comparing the results of QTLs analyses performed in this thesis with those previously carried out in other Solanaceae genera(Grandillo et al. 1999, Ben Chaim et al. 2001[START_REF] Djian-Caporalino | Root-knot nematode (Meloidogyne spp.) resistance genes Me in pepper (Capsicum annuum L.) are clustered on the P9 chromosome Submitted[END_REF], Rao et al. 2003[START_REF] Zygier | QTLs mapping for fruit size and shape in chromosomes 2 and 4 in pepper and a comparison of the pepper QTL map with that of tomato[END_REF] several putative orthologous regions have been identified, in particular for traits referred to the fruit weight, fruit diameter fruit length, fruit shape, flowering earliness and plant height.The present results show that only 10% of the QTLs detected in the YC population have putative correspondent QTLs in both tomato and eggplant, a value in contrast to the 40% of loci detected by Doganlar et al.

  classes of markers are RFLPs, SSRs and SNPs, which are frequently co-dominant, and more informative. The main limiting factor in using RFLPs and SSRs is their low polymorphism within C. annuum, which makes necessary to develop and test many of them for obtaining a low number of useful markers. SNPs, as well, are present in a high number throughout the plant genomes and might also be used for their linkage to functional genes. However, their development is costly and time consuming and this may hamper their use. A possible alternative to the use of new SNPs might arise by the application of RFLPs, COSII and SNPs already mapped in other Solanaceae species. These might also allow to compare different pepper maps with the aim of highlighting the occurrence of reciprocal chromosomal translocations which have taken place in Capsicum speciation. These translocations might be responsible for pseudolinkage phenomenon between loci close to the interchange breakpoint, in particular for chromosome P1 and P8. The use of telomeric markers will be useful to both saturate and more precisely define the sizes of pepper chromosomes.

  accumulation of resistance alleles to several pathogens (Phythophthora, powdery mildew, potyviruses, CMV, TSWV) and genetic components linked to large fruit or early-vigorous plants will require multiple recombination in the targeted chromosomes -Chromosomes P6 and P7 also cumulate QTLs for both resistance and qualitative traits, but larger genetic distance may favour selection of recombinant individuals. -Chromosome P5 includes only disease resistance QTLs (Phytophthora, CMV, powdery mildew) -Chromosome P8 contains only QTLs for horticultural traits.

Figure 1 :

 1 Figure 1: Maps aligned from the three populations analysed. QTLs position for horticultural and resistance traits together with other resistance genes previously mapped are showed for each chromosome.

L

  'objective de la thèse était de développer une carte intraspecifique a haute résolution du piment (C. annuum. L) pour intégrer l'information génétique de caractères horticulturaux et pour générer des outils pour la sélection multi-caractères chez le piment. La carte a haute résolution a été construite en utilisant une descendance recombinante de 297 lignées F5. Les parents utilisés étaient la variété commerciale Yolo Wonder et la variété épicé Criollo de Morellos 334. Un totale de 597 marqueurs moléculaires (ont été utilisés. La carte trame couvrait 1857 cM avec une distance moyenne entre marqueurs de 5,71 cM. Le bon niveau de résolution dérivait soit de la taille de la population utilisés, soit de l'utilisation d'une génération F5. Une analyse QTL sur 13 caractères horticulturaux liés a caractéristiques des fruits et de la plante a été réalisée, en utilisant soit la populations de cartographie soit deux populations haploïdes doublées dérivées des croisements Perennial X Yolo Wonder et H3 X Vania. Un total de 14 et 6 QTL communes ont été détectées entre les 3 populations en étude. Une analyse de synténie entre tomate, piment pomme de terre et aubergine a été réalisée pour les régions génomiques contrôlant les caractères horticulturaux. Plusieurs régions conservées ont été découvertes, que peuvent avoir été conservées pendant l'évolution et la sélection de ces espèces. En utilisant le « selective genotyping", sous groupes des individus les plus informatives (141, 93, 45 ou 29) ont été identifiés pour réduire les efforts du marquage et du phénotypage. Les résultats démontraient que les souspopulations les plus grandes permettaient de garantir une bonne résolution en cartographie. Au contraire le "selective genotyping" ne ressemblait pas utile pour l'analyse QTL car seulement les QTL a effet fort et avec une valeur de R 2 >30-40% ont été détectées dans les sous-groups considérés.

  Moreover many QTLs detected in pepper seem to be cross specific, and thus not transferable or comparable among pepper crosses and also among species. Furthermore possible orthologous QTLs seem to have

different effects.

[START_REF] Djian-Caporalino | Root-knot nematode (Meloidogyne spp.) resistance genes Me in pepper (Capsicum annuum L.) are clustered on the P9 chromosome Submitted[END_REF]

reported that QTL controlling the fruit shape in eggplant ovs4.1 is a are major fruit/ovary shape QTL in eggplant but their putative orthologs in pepper and tomato have relatively minor effects.

•

  To propose new strategies for Marker Assisted Selection.

	Chapter 1: SSR EST-derived development for
	mapping and phylogenetic studies
	Développement de marqueurs SSR dérives de
	EST pour la cartographie génétique et les études
	phylogénétiques.

Introduction

A range of molecular marker types has been applied to study phylogeny and to construct genetic maps in pepper, and of these, microsatellites

Table 2

 2

	) were removed from the sequence set subjected to automated
	sequence analysis. To avoid an overestimation of specific SSR types, a
	redundancy analysis was performed on the 899 SSR-containing
	sequences, which resolved these into 99 clusters containing 422
	sequences, and 477 singletons. The retention of only one member from
	each cluster produced a non-redundant set of 576 sequences (7.1% of
	the sequences investigated, Table 2), containing 783 SSRs. Of these,
	531 (68%) were mononucleotide motifs, 103 (13%) dinucleotide, 137
	(18%) trinucleotide, 8 (1%) tetranucleotide, 1 penta-and 3
	hexanucleotide (Table 2). The high abundance of mononucleotide SSRs
	is consistent with prior analyses of SSR presence in plant genomes
	(Wang et al. 1994; Cardle et al. 2000; Morgante et al. 2002). Trimeric
	repeats are more common than dimeric ones in the gene-space of both
	human (Subramanian et al. 2003) and a number of plant species (Cardle

Table 5

 5

	. Allele number

Table 2

 2 Overview of the in silico search for SSRs. NR: non-redundant SSR-containing sequences; NA: sequence not aligned with previously developed EST-SSRs.

Table 3

 3 Frequency of repeat motifs. NR: non-redundant SSR-

	containing sequences; NA: sequence not aligned with previously
	developed EST-SSRs.
					Sequence
	SSR motif	Total	NR	NA	s > 1.5
					Kbp
	A/T	903	506	488	35
	C/G	33	25	24	4
	AC/GT	21	16	14	1
	AG/CT	99	60	51	2
	AT/AT	47	27	23	9
	AAC/GTT	20	19	12	1
	AAG/CTT	61	40	36
	AAT/ATT	25	17	14	1
	ACC/GGT	35	15	12	2
	ACG/CTG	4	3	3	-
	ACT/ATG	9	9	9	-
	AGC/CGT	11	11	9	-
	AGG/CCT	13	7	6	-
	AGT/ATC	16	10	10	-
	CCG/CGG	13	6	5	-
	AAAG/CTTT	1	1	1	-
	AAAT/ATTT	4	3	2	1
	AAGG/CCTT	1	1	1	-
	AATT/AATT	3	2	2	-
	ACAT/ATGT	2	1	1	1
	AAGAG/CTCTT	1	1	1	-

Table 4

 4 Occurrence of non-redundant SSRs in a set of ca. 8,000 Allelic variation in 49 informative SSR loci

	Capsicum sequences.
							i. Number of repeats	Total
	SSR motif
		5	6	7	8	9 10 11 12 13 14 15 >15
	A/T	-	-	-	-	-92 50 40 30 20 20 254
	C/G	-	-	-	-	-	8		7	3	1	2	4
	AC/GT	-	9	3			2	1	1
	AG/CT	-20 16 7	2	2		1			1 11
	AT/AT	-10 9	1	1	2		1			1	2
	AAC/GTT	11 4	2	1	1
	AAG/CTT	25 9	3	1	1	1
	AAT/ATT	5	5	4	2				1
	ACC/GGT	11 2		1	1
	ACG/CTG	2	1
	ACT/ATG	7	1	1
	AGC/CGT	7	4
	AGG/CCT	5	2
	AGT/ATC	9		1
	CCG/CGG	4	1	1
	AAAG/CTTT	1
	AAAT/ATTT	1	2
	AAGG/CCTT	1
	AATT/AATT	2
	ACAT/ATGT			1
	AAGAG/CTCTT	1
	AAAAAC/GTTTTT	1
	AACCCG/CTTGGG 1
	ACGAGG/CCTGCT 1

  About 92% of the skewed markers were AFLPs, of which 24 were amplified by EcoRI/MseI PCs, 53 by PstI/MseI PCs and two by SacI/MseI PCs. The remaining distorted markers were one RFLP and one STS marker. For the linkage analysis, markers showing skewed

	). A
	significant (P<0.01) level of segregation distortion occurred at about
	14% of the loci (81 markers), with high (P<0.001) distortion at 45
	markers and very high (P<0.0001) distortion at 36 markers. The
	direction of distortion was towards 'CM334' for 46 loci and towards 'Yolo
	Wonder' for 35.

segregation were classified into: (i) those integrated into the framework map, (ii) those assigned to an

Table 1 .

 1 The complete map involving all 489 markers assigned to LGs is available at http://www.inra.avignon.fr, and the subset of the 45 most Number of polymorphic bands generated by each AFLP primer combination.

	informative	RILs	is	available	on	request	from
	alain.palloix@avignon.inra.fr.

. By applying this method,

[START_REF] Howad | Mapping with a few plants: using selective mapping for microsatellite saturation of the Prunus reference map[END_REF]

identified a subset of six lines out of the 88 used to construct a Prunus reference map. For further mapping saturation, only RIL individuals belonging the subpopulation "A" will be selected, a strategy which should reduce to half the cost and time required for genotyping. Our current results, as previously demonstrated by

[START_REF] Xu | Improving quantitative trait loci mapping resolution in experimental crosses by the use of genotypically selected samples[END_REF]

, show that selective genotyping is an attractive strategy in situations requiring phenotypic testing and QTL mapping.

84

Note:

Table 2 .

 2 SSR primers and the molecular weight of amplicons. * SSRs from Nagy et al. (2004); ** SSRs from Portiset al. (unpublished).

		Size (bp)	280	150/140	231	283	159	344	100	311	186	189	205	217
	GenBank	SSR accession nr°	EPMS747** CO907904	EPMS755** CO912244	EPMS919** AY702979	Hpms 1_1 Lee et al. 2004	Hpms 1_111 Lee et al. 2004	Hpms 1_172 Lee et al. 2004	Hpms 1_214 Lee et al. 2004	Hpms 1_5 Lee et al. 2004	Hpms 1_62 Lee et al. 2004	Hpms 2_13 Lee et al. 2004	Hpms 2_24 Lee et al. 2004	Hpms1-69 Lee et al. 2004
	GenBank	SSR accession nr° Size (bp)	EPMS429* CA525246 174/162	EPMS441* CA847465 118/124	EPMS472* BM061910 293/320	EPMS480* BM062655 256/253	EPMS497* CA522759 251/250	EPMS561** BM068460 114/117	EPMS643** CO908387 212	EPMS649** CO776131_c43 260/240	EPMS650** 250 CO910134	EPMS670** 102 CO910307	EPMS686** 158 CK901658	EPMS694** 238 CO912323	EPMS704** 160/150 CO910889	EPMS725** CO910566
		Size (bp)	300/330	273/260	299/305	326/324	260/256	156/162	149/143	187/185	203/201	174/164	187/184	226/224	256/247	116/108
	GenBank	accession nr°	BM061162	BM064640	BM067271	CA515633	CA516334	CA516439	CA517699	CA519548	CA523427	CA525246	CA525390	CA523208	CA514272	CA517376
		SSR	EPMS310*	EPMS340*	EPMS353*	EPMS372*	EPMS376*	EPMS377*	EPMS386*	EPMS391*	EPMS402*	EPMS409*	EPMS410*	EPMS419*	EPMS421*	EPMS426*

Table 3 .

 3 Chromosome assignment and function (where known) of RFLP and STS markers.

	Pepper	Chromosome	P2	P5	P9	P9	P4	P5	P4	P3	P6	P2	P5	P1	unlinked	P5	P4	P8
	Reference of the sequence	Ganal et al. 1988	Ganal et al. 1988	Ganal et al. 1988	Lefebvre et al. 2002	Ganal et al. 1988	Stintzi et al. 1993	Causse et al. 2004	Livingstone et al. 1999	Livingstone et al. 1999	unpublished data from the INRA	laboratory	http://www.sgn.cornell.edu/	http://www.sgn.cornell.edu/	http://www.sgn.cornell.edu/	http://www.sgn.cornell.edu/	http://www.sgn.cornell.edu/	http://www.sgn.cornell.edu/
	Species of origin of the sequence	for RFLP	Tomato	Tomato	Tomato	Tomato	Tomato	Tobacco	Tomato	Pepper	Pepper	Potato	Tomato	Tomato	Tomato	Tomato	Tomato	Tomato
	Description and Putative function (species)	Hypothetical yeast protein / yeast	Serine Hydroxymethyl Transferase / Arabidopsis	thaliana	Xyloglucan endo-1,4-beta-D-glucanase / Tomato	G subunit of the Vacuolar-type AATPase / Tobacco	Alpha amylase / Potato	Acid class III chitinase-lysozyme / Tobacco	Dehydration-induced protein (Clone LEEB'7-2) /	Arabidopsis thaliana	pepper genomic DNA	pepper genomic DNA	AFLP fragment C45/M51_430.4 from the 'RH'	genotype / Potato	Putative phospholipase / Arabidopsis thaliana	Subtilisin-like proteinase (EC 3.4.21.-) 4 / Tomato	unknown protein / Arabidopsis thaliana	Phosphatidylglycerolphosphate synthase (PGP1) /	Arabidopsis thaliana	S-locus protein kinase family / Arabidopsis thaliana	Guanine nucleotide-exchange protein-like /	Arabidopsis thaliana
	RFLP probe	CD035	CT080	CT100	CT145	CT224	GC015_1	GC207	PG101	PG108	PT001c	T_1430	TG029	TG046	TG123	TG132	TG281

Table 2 :

 2 Means and heritabilities of quantitative traits in the parents, the F1 and the F6.

	Heritability		0.96	0.96	0.97	0.97	0.92	0.84	0.95	0.88	0.94	0.92	0.91	0.9		0.93
	Mean	F6	3.33	77.83	36.98	2.19	4.06	2.85	47.63	56.62	22.06	11.56	1.93	3.68		5.32
	Mean	F1	3.27	81.88	29.98	2.2	2.49	2.46	49.94	52.73	25.1	11.26	2.25	3.39		6.66
	Mean	Criollo de Morelos	1.83	58.83	14.87	3.17	3.68	2.29	38.23	53.07	22.82	12.44	1.85	3.12		6.01
	Mean	Yolo Wonder	5.38	91.47	77.83	1.02	7.45	4	41	60.96	18.01	12.12	1.49	3.86		3.93
	Trait		Logarith of fruit weight Lfw	Fruit length (mm) Frl	Fruit diameter (mm) Frd	Fruit shape Frs	Pericarp thickness (mm) Pet	Number of locules Nle	Pedicel length (mm) Pel	Flowering (days) Flw	Axis length (cm) Axl	Number of leaves Nle	Internode length (cm) Inl	Internode growth time Int	(days)	Axis growth speed (mm/day) Axs

  Mean phenotypic value estimates for each trait are listed in Table3.Correlations between traits are presented in Table4. Differences between the parental lines are close to those observed in the previously

				iii. Perennial X Yolo Wonder population
	Axs	-0.17	0.03	-0.20	0.14	-0.10	0.01	-0.01	-0.08	0.94	0.40	0.68	-0.45
	Int described cross, taking into account that Perennial fruits are even lighter 0.28 0.12 0.27 -0.09 0.20 -0.05 0.26 0.12 -0.39 -0.88 0.34 and narrower than CM334. Differences between parents for plant traits
	Inl are stronger since Perennial displayed a longer primary stem, a higher 0.05 0.14 0.00 0.09 0.06 -0.05 0.21 0.01 0.66 -0.30 number of leaves, and a longer flowering time than Yolo Wonder. The
	Nle PY progeny displayed normal-like distributions for all the traits. The PY -0.16 -0.11 -0.13 0.01 -0.10 0.06 -0.13 0.34 0.50 doubled haploid lines displayed intermediate values between the
	parental lines for all the fruit traits. The PY lines frequently displayed
	Axl transgressive values, particularly when the parental values were close to -0.09 0.03 -0.11 0.08 -0.03 0.02 0.08 0.26
	each-other (Flw, Axl, Int and Axs) (Figure
	Flw	0.23	0.03	0.26	-0.14	0.20	0.03	0.25
	Pel	0.14	0.40	-0.02	0.30	-0.04	-0.22
	Nlo	0.23	-0.29	0.36	-0.46	0.17
	Pet	0.73	0.06	0.68	-0.43
	Frs	-0.31	0.69	-0.64
	Lfw Frl Frd	0.41 0.87	0.06											positive and >0.3	negative and <-0.3
	Trait	Lfw	Frl	Frd	Frs	Pet	Nlo	Pel	Flw	Axl	Nle	Inl	Int	Axs

Table 4 :

 4 97 Means and heritabilities of quantitative traits for the PY population in the parents, the F1 and the DH generations.

	0.95	0.96	0.97	0.87	0.95	0.93	0.88	0.93		0.88
	54.66	24.24	2.41	92.28	37.58	18.77	1.97	4.12		4.78
	79.7	25.7	3.1	70.7	27	15.7	2.1	3.55		3.95
	41.3	7.2	5.74	65.4	23.6	19	1.9	2.65		3.77
	91.47	77.83	1.02	60.69	18	12.1	1.5	3.78		3.82
	Frl	Frd	Frs	Flw	Axl	Nle	Inl		Int		Axs
	Fruit length (mm)	Fruit diameter (mm)	Fruit shape	Flowering (days)	Axis length (cm)	Number of leaves	Internode length (cm)	Mean internode growth time	(days)	Axis growth speed	(mm/day)

Table 8 :

 8 List of QTLs detected in the F6 progeny. Marker indicates the closest marker to te QTL, direction indicates the parent which contributes to increase the numeric value of the trait. LOD values indicates the threshold for declaring the presence of a QTL for each trait at p>0.05. IM and CIM stand for Interval mapping and Composite interval mapping respectively.

		QTL	Marker	Direction	LOD Variation explained Heritability Additive
						Locus	Trait
	Logarithm of	Lfw3.1	e40/m49_198y	Yolo Wonder	5.14	0.11			0.12
	fruit weight	Lfw4.1	p17/m32_240c	Yolo Wonder	9.63	0.15			0.15
	Lod>3.08	Lfw11.1	e41/m61_137c	Yolo Wonder	4.61	0.07			0.1
		Lfw12.1 CIM	e44/m51_263c	Yolo Wonder	4.22	0.05			0.09
		LfwLG15.1	e38/m60_224y	Yolo Wonder	5.03	0.08			0.1
		LfwLG24.1 IM e41/m54_184y	Yolo Wonder	4.49	0.08			0.11
		LfwLG45.1	Epms_402	Yolo Wonder	4.01	0.08	0.48	0.96	0.1
				Criollo de
	Fruit length	Frl3.1	e36/m52_158	Morelos	7.26	0.1			-3.9
	Lod>3.12	Frl4.1	e38/m60_109	Yolo Wonder 17.16	0.21			6.5
		Frl7.1	e41/m61_140c	Yolo Wonder	5.53	0.1			3.43
		FrlLG22.1	e34/m53_181c	Yolo Wonder	5.99	0.1	0.39	0.96	3.95
	Fruit diameter Frd2.1 CIM	CD035	Yolo Wonder	4.73	0.12			2.23
	Lod>3.15	Frd3.1	p14/m39_221y	Yolo Wonder	3.72	0.11			2.17
		Frd4.1	e41/m48_078	Yolo Wonder	4.63	0.05			1.46
		Frd8.1 CIM	p11/m49_274	Yolo Wonder	3.23	0.06			1.38
		Frd10.1	e36/m47_145	Yolo Wonder	3.32	0.07			1.73
		Frd11.1	e41/m61_137c	Yolo Wonder 11.27	0.13			2.34
		Frd12.1 IM	e44/m51_263c	Yolo Wonder	3.43	0.06			1.65
		FrdLG15.1	e38/m60_224	Yolo Wonder	7.64	0.1			2.06
		FrdLG17.1	e38/m61_144	Yolo Wonder	4.74	0.06			1.57
		FrdLG24.1 IM e41/m54_184	Yolo Wonder	4.57	0.08			1.85
		FrdLG25.1	p15/m40_091	Yolo Wonder	6.09	0.07			1.7
		FrdLG37.1	p15/m40_319c	Yolo Wonder	3.94	0.06	0.91	0.97	1.56
				Criollo de
	Fruit shape	Frs2.1 CIM	e36/m52_116	Morelos	3.24	0.04			-0.11
				Criollo de
	Lod>3.12	Frs3.1	e43/m54_256	Morelos	11.75	0.15			-0.22
		Frs4.1	p14/m39_417	Yolo Wonder	4.01	0.05			0.11
		Frs4.2CIM	p25/m45_109	Yolo Wonder	3.83	0.08			0.16
				Criollo de
		Frs10.1	e38/m60_117	Morelos	4.68	0.06			-0.14
				Criollo de
		Frs11.1	e41/m61_270	Morelos	4.41	0.07			-0.13
				Criollo de
		FrsLG17.1	e40/m47_239	Morelos	5.21	0.07			-0.14
				Criollo de
		FrsLG25.1	e41/m54_351	Morelos	3.79	0.06	0.31	0.97	-0.12
	Pericarp
	thickness	Pet3.1	PG101	Yolo Wonder	5.15	0.14			0.24
	Lod>3.06	Pet6.1 IM	p25/m45_185	Yolo Wonder	3.59	0.05			0.15
		Pet10.1	e36/m47_145	Yolo Wonder	6.87	0.09			0.19
		Pet11.1 IM	e41/m61_270	Yolo Wonder	3.69	0.06			0.15
		Pet12.1CIM	e44/m51_263	Yolo Wonder	3.31	0.04			0.13
		PetLG15.1	e38/m60_224y	Yolo Wonder	7.82	0.1			0.2
		PetLG24.1IM e41/m54_184	Yolo Wonder	4.27	0.07			0.18
		PetLG27.1	e40/m49_305	Yolo Wonder	5.75	0.08	0.31	0.92	0.18
	Number of
	loges	Nlo2.1 CIM	e36/m47_146	Yolo Wonder	3.42	0.05			0.08
	Lod>3.00	Nlo8.1	Hpms1_214	Yolo Wonder	3.83	0.06			0.09
		Nlo12.1	e44/m51_263c Yolo Wonder	4.08	0.05			0.08
		Nlo12.2	e36/m47_237	Yolo Wonder	4.88	0.1			0.08
		NloLG17.1 IM e38/m61_144	Yolo Wonder	4.06	0.08			0.1

Table 9 :

 9 QTLs detected in the PY population. Marker indicates the closest marker to te QTL, direction indicates the parent which contributes to increase the numeric value of the trait. LOD values indicates the threshold for declaring the presence of a QTL for each trait at p>0.05. IM and CIM stand for Interval mapping and Composite interval mapping respectively

	Total phenotypic

Table 10 :

 10 QTLs detected in the HV population. Marker indicates the closest marker to te QTL, direction indicates the parent which contributes to increase the numeric value of the trait. LOD values indicates the threshold for declaring the presence of a QTL for each trait at p>0.05. IM and CIM stand for Interval mapping and Composite interval mapping respectively 139 Receptivity Using the original population, one QTLs was found on chromosome P5. The use of the subpopulation composed of 141 individuals allowed to detect the same QTL with a R 2 = 0.43. By using the subpopulation of 93 individuals we found the same QTL with a R 2 = 0.35. Only the resistant Criollo de Morelos alleles increased the resistance.

		QTL	Marker	Direction	LOD	Variation explained Heritability Additive
						Locus	Trait
	Logarithm of fruit	Lfw2.1	e40/m48_229v Vania	3.83	0.24			0.34
	weight	Lfw3.1	PG101	Vania	3.26	0.15			0.27
	Lod>3.01	Lfw11.1	B10_0.9	Vania	6.60	0.28			0.38
		Lfw11.2	CT101	Vania	9.67	0.26	0.47	0.97	0.36
	Fruit length	Frl1.1CIM TG370	H3	3.26	0.1			-8.93
	Lod>3.04	Frl2.1CIM TLL080	Vania	3.15	0.13			10.42
		Frl7.1CIM COO088	Vania	3.86	0.12			10
		Frl9.1IM	P09_0.25	Vania	2.84	0.12			10.02
		Frl9.2	Ae11_1.3	Vania	4.66	0.15	0.29	0.94	11.13
	Fruit diameter	Frd2.1 IM e40/m48_229v Vania	3.62	0.22			7.06
	Lod>2.87	Frd3.1	007_075	Vania	4.49	0.11			4.9
		Frd8.1CIM TG017	Vania	3.50	0.08			4.25
		Frd10.1CIM e40/m48_227v Vania	3.49	0.08			4.25
		Frd11.1	TG104	Vania	9.98	0.26	0.58	0.95	7.99
	Fruit shape	Frs1.1CIM P13/m47_361h	H3	3.24	0.1			-0.3
	Lod>2.98	Frs3.1	D11_0.6h	H3	4.65	0.15			-0.38
		Frs10.1CIM e40m49_227v	H3	3.01	0.08			-0.28
		Frs11.1	B10_09	H3	5.21	0.19	0.48	0.94	-0.42
	Peduncule length Pel6.1CIM e36/m59_380h	H3	4.89	0.13			-6.1
	Lod>3.06	Pel8.1	e36/m49_125h Vania	9.87	0.27			8.56

Table 11 :

 11 QTL detection in the original and reduced populations obtained by selective sampling.

Table 12 :

 12 Parental alleles influencing the horticultural traits analysed in the three progenies. Letters indicate Yolo Wonder (Y), Criolo de Morelos 334 (C), Perennial (P), Vania (V), H3 (H), while na stands for "not available".

	Population

  . Thus C. annuum types were clustered together, and two sub-clusters corresponding to fruit morphology characteristics e.g: small fruited types and large-fruited ones, could be recognised as previously reported. The cluster closest to the annuum group contained both frutescens and chinense types, while a less genetically related cluster contained the remaining wild Capsicum species baccatum (vars. baccatum and pendulum), praetermissum, chacoense, eximium and pubescens.

	The high level of inter-specific SSR transferability achieved across the
	eight Capsicum species included in the present study mirrors that
	experienced in other plant contexts (reviewed by Varshney et al. 2002),
	which have confirmed that EST-SSRs are highly conserved across
	species of the same genus

  as shown between potato and tomato(Milboune et al. 1998). However, recent results (I. Nagy pers. communication) showed that SSR markers are cross-species transferable in the Solanaceae family as previously demonstrated by[START_REF] Provan | Microsatellite analysis of relationships within cultivated potato (Solanum tuberosum)[END_REF] and[START_REF] Smulders | Use of short microsatellites from database sequences to generate polymorphism among Lycopersicon esculentum cultivars and accessions of other Lycopersicon species[END_REF]. On the whole, the present results confirmed that the newly-derived EST-SSRs are BenChaim et al. 2001; Rao et al. 2003, Zygier et al.

			inter-specific transferability as previously demonstrated in
			other plants (Scott et al. 2000, Varshney et al. 2002)
		v)	the stringent threshold applied (LOD > 8 and r < 0.1) to
			declare linkage groups consistently increased the confidence
			in marker position and relative order;
	informative for phylogenetic and mapping studies; furthermore, they are vi) because of the high percentage of homozygosity (93.75%
	present within the transcriptome and may represent a valuable tool for theoretically and an observed average of 92.43%± 3.76%),
	mapping genes of known function. the developed RIL population is immortalised and makes it
			possible the replication of phenotypic assays across different
	The intra-specific genetic linkage map developed in this thesis may environments; thus it will supply robust estimates of trait
	be considered as the new reference map for the following reasons: means making the identification of quantitative trait loci more
	i)	it has a good level of resolution, both because the population efficient and reliable.
		is larger than never used in pepper, and because the use of The use of stringent threshold in declaring linkage groups generated 49
		an F5 generation allowed more meioses to be involved than LG of which 23 were successfully assigned to the 12 haploid pepper
		in the previous F2 or doubled haploid populations used for chromosomes, while 26 remain still unassigned. Maps comparison was
		mapping; possible thanks to 32 shared markers, which allowed the assignment of
	ii)	the use of an intra-specific progeny makes it possible to
		reduce the frequency of skewed segregation, thus increasing
		mapping precision;
	iii)	the overall length of the map is 1857 cM, a value analogous alignment was successful for all the chromosomes except P1 and P8
		to the one of 1832 cM reported for the integrated map from interspecific crosses, as previously reported in chapter 2.
		developed by Paran et al. (2004), but significantly greater
		than the one of 1466 cM based on RILs and recently 1.2 GENOMIC ORGANIZATION OF QTLS FOR HORTICULTURAL
		published by Ogundiwin et al. (2005); TRAITS
	iv)	the map contains mainly AFLP markers, but also a few SSR
		and RFLP markers, which are valuable as anchor markers. In pepper, QTL analyses were previously mainly focused on
		Although the few RFLP markers did not permit a precise genetics of resistance to biotic stresses (Grube et al. 2000b, djian
		alignment with tomato maps, SSR markers will promote Caporalino et al 2006). QTL analyses of horticultural traits (fruits and
		alignment with other pepper maps due to their high level of plant phenotype) was restricted to a few crosses and plant traits were
		poorly considered (

23

LGs with regions on the pre-existing maps. All common AFLP markers mapped at the same location, thus confirming their locusspecificity (Rouppe van der

Voort et al. 1997;[START_REF] Lefebvre | Towards the saturation of the pepper linkage map by alignment of three intraspecific maps including known-function genes[END_REF]

. The

Acknowledgements

Vorrei ringraziare il Prof. Sergio Lanteri per l'aiuto e la disponibilità dimostrata, per avermi offerto l'opportunità del dottorato di ricerca e per avermi sostenuto durante questi 3 anni importanti per la mia formazione.

Ringrazio il

Dott. Ezio Portis, per la sua collaborazione, per i suoi insegnamenti in laboratorio e per le partite di calcetto. Ringrazio il Dott. Alberto Acquadro, sempre disponibile. I tre anni passati nello stesso ufficio sono stati piacevoli, anche se un po' noiosi quando mi chiedevi di abbassare la musica. Mi spiace che tu abbia cambiato d'ufficio ma ti ringrazio per avermelo svuotato, adesso sembra più grande e molto più pulito. Ringrazio la Dott.ssa Cinzia Comino, Il Dott. Francesco "Paguro" Magurno (in arte Checco), il Dott. Andrea Moglia per l'aiuto ed il tempo passato assieme. Infine ringrazio il Dott. Gialuigi Bigio e la Dott.ssa Sara Falvo. Je voudrais remercier Alain Palloix pour m'avoir aidé pendant les moments passé a l'INRA, pour m'avoir appris pleine de nouvelles choses, pour les récits de ses voyages, des ses randonnées et pour entre toujours pour m'écouter. Je remercie Véronique Lefebvre pour m'avoir aidé elle aussi pendant mon séjour a Avignon, tu m'a appris beaucoup de choses.

QTLs detection in the subpopulations selected from the recombinant inbred progeny YC

In order to compare the performance of QTL detection in reduced populations obtained by selective sampling, QTL analysis was performed in the 2 sub-populations A (141 inbred lines) and B (93 inbred lines) that were sampled by means of MapPop software [START_REF] Brown | MapPop 1.0: Software for selective mapping and bin mapping[END_REF] from the recombinant inbred lines from the YC population (297 inbred lines). Only three traits were submitted to the analysis: one fruit trait (Lfw) that was controlled by QTls with variable R 2 values (0.15 to 0.08), one plant trait (Axl) controlled by QTLs with low R 2 values (0.10 to 0.6), and one disease resistance trait that was shown to be controlled by a high effect QTL (R 2 =0.53) and minor QTLs (R 2 from 0.12 to 0.03) (Table 11).

Logarithm of fruit weight

Of the 7 QTLs detected with 297 individuals, only 3 (Lfw3.1, Lfw4.1 and LfwLG15.1) were found using the subpopulations of 141 plants. Lfw3.1

is the most important with a R 2 = 0.18 while total phenotypic variation explained was 30%. Only Yolo Wonder alleles contributed to the trait.

3 QTLs were also found using 93 individuals (Lfw4.1IM, Lfw11.1IM and LfwLG15.1) with LfwLg15.1being the most important with a R 2 = 0.18.

Total phenotypic variability explained by those QTLs was 23%.

Axis Length

Of the 5 QTLs previously found using 297, no QTLs were detected using 141 individuals. Surprisingly using 93 individuals one QTL on chromosome 12 was found with R 2 = 0.2. Abstract