Search

Glucosinolates (GSs) were analyzed in 56 accessions of Brassica rapa grown in the greenhouse. Eight different glucosinolates were identified in the Brassica rapa group. They are the aliphatic glucosinolates progoitrin (PRO), gluconapin (NAP), glucobrassicanapin (GBN), the indolyl glucosinolates 4-hydroxyglucobrassicin (4OH), glucobrassicin (GBC), 4-methoxyglucobrassicin (4ME), neoglucobrassicin (NEO) and the aromatic glucosinolate gluconasturtiin (NAS). Gluconapin, glucobrassicanapin, progoitrin and gluconasturtiin are the most abundant GSs in the Brassica rapa, but there is considerable variation in content among accessions. The total glucosinolate contents in Brassica rapa group varied substantially between the different accessions. The highest amount of GSs (361 µmol/100 g FW) was observed in leaves of vegetable turnip, followed by rapid cycling and yellow sarson, with the amount of 200 and 178 µmol/100 g FW respectively. Whereas the lowest GSs content was found in turnip greens (20.8 µmol/100 g FW) and Wutacai (22.6 µmol/100 g FW). The total aliphatic GSs proportion varied from 50 to 90% of the total GS, while generally the content of indolyl glucosinoloates, especially 4OH glucobrassicin and neoglucobrassicin is low. Gluconasturtiin was found in relatively high concentrations in komastsuna (14.6 µmol/100 g FW), yellow sarson (7.1 µmol/ 100 g FW) and constitutes as much as 24% of the total amount of glucosinolates. Relatively high amounts of gluconapin (281 mmol/100 g FW) and glucobrassicanapin (60.0 mmol/100 g FW) were observed in the leaves of vegetable turnip. Compared with the Brassica oleracea group, Brassica rapa lacks glucoraphanin and sinigrin but contains gluconapin and glucobrassicanapin. Variations in glucosinolate content among genotypes suggest differences in their health-promoting properties and the opportunity for enhancement of their levels through breeding or genetic modification.

Tomato (Lycopersicon esculentum) is susceptible to the powdery mildew Oidium lycopersici, but several wild relatives such as Lycopersicon parviflorum G1.1601 are completely resistant. An F2 population from a cross of Lycopersicon esculentum cv. Moneymaker × Lycopersicon parviflorum G1.1601 was used to map the O. lycopersici resistance by using amplified fragment length polymorphism markers. The resistance was controlled by three quantitative trait loci (QTLs). Ol-qtl1 is on chromosome 6 in the same region as the Ol-1 locus, which is involved in a hypersensitive resistance response to O. lycopersici. Ol-qtl2 and Ol-qtl3 are located on chromosome 12, separated by 25 cM, in the vicinity of the Lv locus conferring resistance to another powdery mildew species, Leveillula taurica. The three QTLs, jointly explaining 68% of the phenotypic variation, were confirmed by testing F3 progenies. A set of polymerase chain reaction-based cleaved amplified polymorphic sequence and sequence characterized amplified region markers was generated for efficient monitoring of the target QTL genomic regions in marker assisted selection. The possible relationship between genes underlying major and partial resistance for tomato powdery mildew is discussed.

Background Flowering time is an important trait in Brassica rapa crops. FLOWERING LOCUS C (FLC) is a MADS-box transcription factor that acts as a potent repressor of flowering. Expression of FLC is silenced when plants are exposed to low temperature, which activates flowering. There are four copies of FLC in B. rapa. Analyses of different segregating populations have suggested that BraA.FLC.a (BrFLC1) and BraA.FLC.b (BrFLC2) play major roles in controlling flowering time in B. rapa. Results We analyzed the BrFLC2 sequence in nine B. rapa accessions, and identified a 57-bp insertion/deletion (InDel) across exon 4 and intron 4 resulting in a non-functional allele. In total, three types of transcripts were identified for this mutated BrFLC2 allele. The InDel was used to develop a PCR-based marker, which was used to screen a collection of 159 B. rapa accessions. The deletion genotype was present only in oil-type B. rapa, including ssp. oleifera and ssp. tricolaris, and not in other subspecies. The deletion genotype was significantly correlated with variation in flowering time. In contrast, the reported splicing site variation in BrFLC1, which also leads to a non-functional locus, was detected but not correlated with variation in flowering time in oil-type B. rapa, although it was correlated with variation in flowering time in vegetable-type B. rapa. Conclusions Our results suggest that the naturally occurring deletion mutation across exon 4 and intron 4 in BrFLC2 gene contributes greatly to variation in flowering time in oil-type B. rapa. The observed different relationship between BrFLC1 or BrFLC2 and flowering time variation indicates that the control of flowering time has evolved separately between oil-type and vegetable-type B. rapa groups.

As a consequence of a sessile lifestyle, plants are constantly facing a fluctuating environment. In order to both profit maximally and protect themselves from these environmental cues, plants evolved ways to sense and respond to signals. Ambient temperature is one of the cues for which plants have acquired a strategy to enhance their chance of survival and reproduction. Small changes in ambient temperature can have major effects on plant architecture and development, such as the transition from the vegetative to the reproductive flowering phase. The moment of flowering is an important event in the life cycle of a plant, since reproductive success depends on it. In Chapter 1, I introduced the concept of alternative splicing, a molecular mechanism with a pivotal role in ambient temperature regulation of flowering time. In the model plant Arabidopsis thaliana, approximately 60% of the intron-containing genes show alternative splicing. Gene splicing varies depending on developmental stage and tissue type, but also environmental changes trigger differential splicing. Splicing is conducted by a large cellular machinery called the spliceosome, which recognizes intron-defining sequences and other cis-regulatory elements acting as splicing enhancers or silencers. Moreover, factors like chromatin structure, histone marks, RNA polymerase II (polII) elongation speed and the secondary structure of the pre-mRNA all play a role in the splicing outcome. Due to alternative splicing, a single gene can yield various transcripts. However, this does not cause an equal expansion of the proteome. Part of the transcripts are targeted for nonsense-mediated decay, or will be translated into unstable proteins. This is a way of regulating gene expression at the post-transcriptional or –translational level. Other transcripts will be translated into functional proteins that may be structurally and functionally different. Hence, alternative splicing creates additional complexity in the transcriptome, providing plants with molecular tools to respond to their environment, including the translation of ambient temperature alterations into a flowering time response. In Chapter 2, we reviewed the current knowledge on molecular mechanisms that control the ambient-temperature directed flowering time pathway in the plant model species Arabidopsis thaliana. Several different mechanisms have been proposed, like alternative splicing of FLOWERING LOCUS M (FLM) (described in Chapter 4) and protein degradation of SHORT VEGETATIVE PHASE (SVP), two mechanisms that probably work in a cooperative manner to release floral repression at higher ambient temperatures. Another mechanism that is involved at high ambient temperature is the replacement of the canonical histone H2A by the variant H2A.Z. As a consequence of this replacement, chromatin becomes less tightly wrapped around the nucleosomes, which allows transcription of flowering time activators, such as PHYTOCHROME INTERACTING FACTOR 4 (PIF4). Lastly, we discuss microRNAs (miRNA) that can either repress or activate flowering (miR156 and miR172, respectively). These miRNAs have been proposed to be regulated by low and high ambient temperature. However, due to the lack of mutant analyses, more research is necessary to show the true involvement of these factors. Altogether, there are several mechanisms acting partly in cooperation to regulate thermosensitive floral timing. In Chapter 3, we analysed ambient temperature-directed alternative splicing events that occur after a temperature shift by RNAseq. We performed the experiment in two different accessions of A. thaliana, and in one variant of B. oleracea (cauliflower). We showed that flowering time genes are overrepresented amongst the ambient temperature induced alternatively spliced genes, but also genes encoding components of the splicing machinery itself, indicating that alternative splicing is one of the potential mechanisms by which plants are able to sense temperature and adapt floral timing. Analysis of a mutant for one of these alternatively-spliced splicing related factors, ATU2AF65A, showed a temperature-dependent flowering time phenotype, confirming its proposed role in the flowering time response upon temperature fluctuations. Based on these findings, we proposed a two-step model in which splicing related genes are targeted for differential splicing upon ambient temperature fluctuations, which results in changes in the composition of the spliceosome, causing differential splicing of downstream genes that affect the development and architecture of the plant, including flowering time. In Chapter 4, we investigated the molecular mode-of-action of FLM, one of the differentially spliced flowering time regulating genes that we identified in Chapter 3. We showed that in A. thaliana Col-0, the main splice forms of FLM are FLMβ and FLMδ. FLMβ forms an obligate heterodimer with SVP, and this complex represses floral integrators like SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1 (SOC1) by binding to the regulatory regions of these genes. FLMδ also dimerizes with SVP, but this complex is not able to bind to DNA. When temperature rises, more FLMδ is produced at the cost of FLMβ. Hence, less repressive complexes can be formed. However, the fact that FLMδ is still able to binds SVP makes it function as a dominant negative form, titrating out SVP and preventing repressive SVP/FLMβ-complex formation. Chapter 5 is a short comment written to clarify the concept of thermoplasticity in flowering time control. Occasionally, this concept is confused with adaptation to different ambient temperature environments on the long term. Thermoplasticity is the ability to adapt flowering time to fluctuations in ambient temperature within one life cycle. Furthermore, some genes have been marked as players in the ambient temperature response, whereas these appear to be general flowering repressors or activators, affecting flowering time in a similar manner at low and high ambient temperature. In order to interpret novel findings on thermosensitive flowering time control, it is essential to distinguish between these various concepts. In chapter 6, we unveiled the first indications that differential splicing of FLM can be caused by differences in polymerase II elongation rate. We mimicked a situation in which FLM is transcribed at a higher rate, by expressing the genomic FLM gene under a strong artificial promoter. Preliminary results showed that plants harbouring this construct have altered flowering time and temperature-responsiveness, which can be explained by the altered FLMβ/FLMδ ratio that we observed. In chapter 7, we assessed the functional conservation between FLM and closely related genes at the intraspecific level in A. thaliana. FLM (also called MAF1) is a member of the FLC-clade, that consists of FLC, FLM and MAF2-5. FLC is widely known for its function in the vernalization pathway, whereas MAF2 has been shown to regulate flowering time through alternative splicing in a way very similar to FLM. For the other MAF genes, not much is known. We showed that all of these genes produce splicing isoforms that function in a more or less similar way to FLM and MAF2. Despite the high functional conservation at the intraspecific level, FLM and MAF orthologues are not widely present. Through synteny analysis, we showed that FLM and MAF2 are very recent genes, which are only present in a small group of Brassicaceae species. MAF3-5 originated less recently, but are not present outside the Brassicaceae. For FLC, it was previously shown that it originated from an ancestor of the seed plants, and in many plant species belonging to other families, presence of more than one FLC-like gene has been reported. This raises the question what the function of these genes is. In tomato, we showed that the FLC-like gene MBP8 becomes differentially spliced upon temperature changes, suggesting a function in the ambient temperature pathway. A binding assay showed high similarities of the different MBP8 isoforms to FLM and MAF isoforms, but suggests a slightly different functionality, since all three isoforms showed binding to the DNA. Further research is necessary to confirm the role of MBP8 in thermosensitive flowering time control, and elucidate the functionality of the different splice forms. In Chapter 8, I discussed the finding of this thesis in a broader perspective, and make suggestions for future research. Over the last few years, several mechanisms that act in the temperature-directed floral pathway have been revealed. In this thesis, we showed that alternative splicing plays an important role, and we demonstrated how temperature may affect the splicing outcome directly through the effect of temperature on transcription elongation rate. It is becoming clear that most likely a single thermosensor does not exist in plants, and a model in which temperature is sensed through thermodynamic properties of DNA, RNA and proteins, is gaining support. Future research is assigned to the exiting task to elucidate the exact mechanisms by which temperature-sensing is achieved in different plant species and to determine how conserved the currently identified molecular mechanisms are.

Summary Seed is the basic and most critical input for seed propagated agricultural crops: seed quality and seedling vigour determine plant establishment, growth and development in both natural and agricultural ecosystems. Seed quality and seedling vigour are mainly determined by the interactions of the following three components: genetic background, physiological quality and the environmental conditions during seed set, seed ripening, storage, seed germination and early seedling development. In the past, many efforts have been made to improve seed germination and seedling vigour by optimizing physiological and environmental factors (non-genetic factors); however, the paradigm has shifted to investigate genetic factors and to use these to improve crop performance by plant breeding. The aim of this thesis is to unravel the genetics of seed germination and seedling vigour under different conditions in Brassica rapa, using a systems genetics approach. Studies in many crop species have reported that seed germination and seedling vigour traits are governed by many genes and are strongly affected by environmental conditions. As salinity stress is becoming one of the most important abiotic stresses affecting crop growth and yield, we studied the genetics of seed germination and seedling vigour under neutral and salt stress conditions. For a number of crops, it has been established that larger seed size and higher seed weight indicate more reserve food and contribute positively to seedling establishment. Therefore, our hypothesis for this thesis is that transcriptional regulation of genes during seed development determines the composition and content of seed reserves, and that these seed reserves play a major role in seed germination and seedling growth, especially at the heterotrophic stage under optimal and sub-optimal conditions. B. rapa is an extremely diverse Brassica species which includes, besides many diverse leafy vegetable types and turnips, also oilseed crops. Brassica seeds are of high economic importance for several reasons. They are the starting point of the life cycle of the crop, but also they are directly used as sources of vegetable oil or condiments. At present, B. napus is the most important source of vegetable oil worldwide, but B. rapa is often used for introgression breeding to broaden its narrow genetic base resulting in genetic improvements. Therefore, the acquired knowledge is also useful for the scientific community and plant breeders working in B. napus and other Brassica species. In Chapter 2 we evaluated the genetic diversity of a B. rapa core collection of 168 accessions representing different crop types and geographic origins. Using the Bayesian cluster analysis software STRUCTURE, we identified four subpopulations: subpopulation 1 with accessions of Indian origin, spring oil, yellow sarson and rapid cycling; subpopulation 2 consisting of several types from Asian origins: pak choi, winter oil, mizuna, mibuna, komasuna, turnip green, oil rape and Asian turnip; subpopulation 3, which included mainly accessions of Chinese cabbage and subpopulation 4 with mostly vegetable turnip, fodder turnip and brocoletto accessions from European origin. The geographical distribution of the accessions was very much congruent with genetic, metabolic and morphological diversity. This initial study was followed by association studies for secondary metabolites from the tocopherol and carotenoids pathways, using the population structure of these four subpopulations as a correction term to control for spurious marker-trait associations (Chapter 2). Additionally, we used a machine learning approach, Random Forest (RF) regression, to find marker-trait associations. We chose the RF approach as it can handle large numbers of variables (markers, metabolites, transcript abundance) in combination with relatively small sample sets of accessions, to show its perspectives for application to the increasing amounts of data available through the different ~omics technologies. In our analysis, the markers showing significant association with metabolites identified by the RF approach overlapped with markers obtained from association mapping. Those markers could potentially be used for marker-assisted selection (MAS) in breeding for these secondary metabolites in different morphotypes or sub-populations. Knowledge of genetic distance as evaluated in this chapter allowed the choice of parents to create a segregating population for QTL analyses by maximizing genetic variation between the parents. In Chapter 4, a doubled haploid (DH) population from a cross of genetically diverse morphotypes of B. rapa, an oil-type yellow sarson (YS143) and a vegetable pak choi (PC175) (Chapter 2), was used to evaluate the genetic basis of seed germination and seedling vigour traits under both non-stress and salt stress conditions. The yellow sarson parent had larger seed size and higher thousand-seed weight than the pak choi parent, and displayed earlier onset, higher uniformity in germination, faster germination and maximum germination, and higher root- and shoot- lengths and biomass under both non-stress and salt stress conditions. Positive correlations of thousand-seed weight with earliness, speed and uniformity of germination and maximum germination percentage, supports that larger seeds germinate earlier, faster, more uniformly and to a higher maximum germination percentage than smaller seeds. Thus, we conclude that yellow sarson had higher seed quality and seedling vigour than pak choi. However yellow sarson also contributed negative alleles to seed germination, as illustrated by its allele of the QTL at A05 which decreases the uniformity of seed germination. In addition we also observed that yellow sarson seedling growth was more affected by salt stress than pak choi. All traits were scored over the DH population, and this clearly showed transgressive variation for most traits. Eight QTL hotspots were identified for seed weight, seed germination, and root and shoot lengths. A QTL hotspot for seed germination on A02 co-located with a homologue of the FLOWERING LOCUS C (BrFLC2) genes and its cis-acting expression QTL (cis-eQTL). FLC2 (BrFLC2 in B. rapa) is an important repressor of flowering time in both A. thaliana and B. rapa and recently, FLC2 was reported for its pleiotropic effect on seed germination in A. thaliana. A QTL hotspot on A05 with salt stress specific QTL co-located with the FATTY ACID DESATURASE 2 (BrFAD2) gene and its cis-eQTL. Besides the role of FAD2 in fatty acid desaturation, the up-regulation of this gene was associated with enhanced seed germination and hypocotyl elongation under salinity in B. napus (BnFAD2) and A. thaliana (FAD2). We observed epistatic interactions between the QTL hotspots at the BrFLC2 and BrFAD2 loci, and between other QTL hotspots. Seed development is regulated by many dynamic metabolic processes controlled by complex networks of spatially and temporally expressed genes. Therefore, morphological characteristics and the transcriptional signatures of developing seeds from yellow- and brown/black-seeded genotypes were studied to get to know the timing of key metabolic processes, to explore the major transcriptional differences and to identify the optimum stage for a genetical genomics study for B. rapa seed traits (Chapter 3). This is the first study of genome-wide profiling of transcript abundance during seed development in B. rapa. Most transcriptional changes occurred between 25 and 35 days after pollination (between the bent-cotyledon stage and the stage when the embryo fully fills the seed), which is later than in the related species B. napus. A weighted gene co-expression network analysis (WGCNA) identified 47 gene modules with different co-expression patterns, of which 17 showed a genotype effect, 4 modules a time effect during seed development and 6 modules both genotype and time effects. Based on the number of genes in gene modules, the predominant variation in gene expression was according to developmental stages rather than morphotype differences. We identified 17 putative cis-regulatory elements (motifs) for four co-regulated gene clusters of genes related to lipid metabolism. The identification of key physiological events, major expression patterns, and putative cis-regulatory elements provides useful information to construct gene regulatory networks in B. rapa developing seeds and provides a starting point for a genetical genomics study of fatty acid composition and additional seed traits in Chapter 5. Since Brassica seeds are sources of vegetable oil, genetic studies of the gene regulatory mechanisms underlying lipid metabolism is of high importance, not only in relation to seed and seedling vigour, but also for Brassica oilseed breeding. In Chapter 5, an integrative approach of QTL mapping for fatty acids composition and for transcript abundance (eQTL) of genes related to lipid metabolism, together with gene co-expression networks was used to unravel the genetic regulation of seed fatty acid composition in the DH population of B. rapa. In this study, a confounding effect of flowering time variation was observed on fatty acid QTLs (metabolite level) at linkage group A02 and of seed colour variation on eQTLs (transcript level) at linkage group A09. At A02, fatty acid QTLs from 2009 seeds co-locate with the genetic position of a gene-targeted marker for BrFLC2, its cis-QTL, and a major flowering time QTL. Flowering time variation is very obvious in this DH population and the BrFLC2 gene at A02 (16.7 cM) is the major regulator of flowering time, with a non-functional allele in the yellow sarson parent. When QTL analysis was performed on seeds from 2011, from DH lines that flowered synchronously due to staggered sowing, this fatty acid QTL hotspot disappeared. The 2011 seed lot was used for further analysis combining fatty acid QTLs with eQTLs in this study. On A09, a large trans-eQTL hotspot was co-localized with a major seed colour QTL, in the region where the causal gene, the bHLH transcription factor BrTT8, was cloned. The role of this gene in seed colour development was functionally proven in B. rapa. As the yellow sarson and pak choi parents of this population have contrasting seed coat colour (Chapter 3) the DH lines segregated for seed colour. When seed colour variation was used as a co-variate in our statistical model, we could exclude its confounding effect on eQTL mapping. We compared the fatty acid QTL and eQTL results from the analyses before and after seed colour correction and later discuss the results from the analysis after correction. The distribution of major QTLs for fatty acids showed a relationship with the types of fatty acids: linkage group A03 contained major QTLs for monounsaturated fatty acids (MUFAs), A04 for saturated fatty acids (SFAs) and A05 for polyunsaturated fatty acids (PUFAs). Using a genetical genomics approach, eQTL hotspots were found at major fatty acid QTLs on A03, A04 and A05 and on A09. Finally, an eQTL-guided gene co-expression network of lipid metabolism related genes showed major hubs at the genes BrPLA2-ALPHA, BrWD-40, a number of seed storage protein genes and a transcription factor BrMD-2, suggesting essential roles of these genes in lipid metabolism. Several genes, such as BrFAE1, BrTAG1, BrFAD2, BrFAD5, BrFAD7, which were reported as important genes for fatty acid composition in seeds in other studies of related species, had relatively lower degrees of connection in the networks. However their cis-eQTLs co-localized with specific fatty acid QTLs, making them candidate genes for the observed variation. We hypothesize that these play a role in modifying fatty acid content or composition across genotypes, rather than playing essential roles in the pathway itself. These results suggest the need of a global study of lipid metabolism rather than a strict focus on the fatty acid biosynthesis pathway per se. This study gives a starting point for understanding the genetic regulation of lipid metabolism, by identification of a number of key regulatory genes, identified as major hub genes, and candidate genes for fatty acid QTLs. In the final chapter (Chapter 6) we summarize and critically discuss the relationships among phenotypic traits, metabolites and expression variation as well as the co-localization of QTLs from these different levels. In this thesis, we developed methodology to integrate transcriptomics and metabolomics data sets and to construct gene regulatory networks related to major fatty acids, and found a set of (possible) candidate genes involved in lipid metabolism. In the future, we recommend to integrate the genome-wide transcriptome data set with all major seed metabolites and phenotypic data on seed and seedling vigour to directly link all three components: transcriptome, metabolome and phenotypic traits, and ultimately expand the knowledge on the genetic regulation of seed metabolites, seed quality and seedling vigour in B. rapa to other Brassica species.

A significant group of plants found in the Croatian native flora belongs to the tribe Alysseae which comprises seven genera: Alyssoides, Alyssum, Aurinia, Berteroa, Clypeola, Degenia and Fibigia. The genus Aurinia comprises 12 taxa among which Aurinia sinuata (L.) Griseb. and A. leucadea (Guss.) C. Koch represent two endemic species wild-growing in Croatia [1]. These plants can be found in mountainous areas of Central and Southern Europe, Russia and Turkey. Degenia velebitica (Degen) Hayek and Fibigia triquetra (DC.) Boiss. ex Prantl are rare Croatian stenoendemic species representing tertiary relicts. Natural area of D. velebitica, the only species of the genus Degenia, is restricted to only several localities on the South and Mid Velebit massif. F. triquetra, sometimes confused with D. velebitica, is one of two species in the genus Fibigia, wild-growing on rocky grounds of Southern Dalmatia. Glucosinolates (GLs) represent molecular tags of the order Brassicales. Plant species that contain high concentrations of a single or a small number of GLs represent one of the most suitable sources for the extraction and purification of fair amounts of these compounds. Thus, the aim of this study was to characterize and quantify GLs in different plant parts. GLs were characterized and quantified according to the ISO 9167-1 official method based on the HPLC analysis of desulfo-GLs and by GC/MS analysis of the volatile fractions obtained after enzyme hydrolysis.

Background Phytochemicals in plant-based foods have been linked to a reduced incidence and progression of diseases. Glucosinolates (GLs) are phytochemicals that are typical for Brassicaand other Cruciferousplants, such as cabbage, broccoli, Brussels sprouts, Chinese cabbage, mustard and horseradish. The intake of GLs has been associated with lowered risks of several types of cancer and other diseases. To reach a high level of GLs in the vegetables at the stage of consumption, research along the food chain aims to increase the concentrations of certain GLs and to lower the losses during food processing; however, effects of the different steps in the food chain are mostly investigated separately. In this thesis an interdisciplinary approach, combining food science and plant science, was applied to explore the possibilities to retain GLs throughout the food chain. The objective of this thesis was to investigate genetic effects related to GL degradation during food processing in order to test if food processing parameters can be used as phenotypic traits and breed for vegetables with improved GL retention. Methods One challenge of integrating plant science and food science is the high number of samples to be analysed to apply quantitative genetics to food technological traits. The analysis of GLs, as desulpho-GLs, was optimized to reach accurate results using a high throughput method. Kinetic modelling was applied to describe GL thermal degradation in a quantitative way, therefore an appropriate model was identified. Furthermore, genetic and environmental effects of GL thermal degradation were investigated in a broccoli and a Chinese kale genotype in two seasons. GL thermal degradation was determined in a segregating population, developed by crossing the broccoli and Chinese kale genotype investigated in the previous study. Thermal degradation rate constants were combined with molecular marker information to identify genetic regions associated with GL thermal degradation (quantitative trait loci). Moreover, a subset of the segregating population was tested for environmental variation. An untargeted metabolomics approach was applied to test if metabolites are associated with the thermal degradation rate constants and hence influence thermal degradation. Results The desulphation procedure applied to determine GLs as desulpho-GLs is crucial for the analytical result. For the first time an inverse effect of the sulphatase concentration on the peak area of a GL, glucotropaeolin, which is often used as internal standard, was shown, leading to a substantial overestimation of GL concentrations. We recommend the application of a purified sulphatase preparation to obtain accurate results for a broad range of samples. A first order kinetic model was identified to be appropriate to describe GL thermal degradation in two seasons. The resulting degradation rate constants (kdvalues) of chemically identical GLs did not differ between the broccoli and the Chinese kale genotype when grown in the same season, but were strongly affected by the season (20% to 80% difference). Despite the degradation rate constants of chemical identical GLs did not differ in the parental genotypes of the segregating population, rate constants varied 3-fold throughout the population for most GLs. Quantitative trait loci (QTL) were identified for the degradation of two different GLs (25% and 12% explained variation). A co-localization of the QTL and correlations between the rate constants of different GLs indicate that similar factors in the plant matrix influence GL degradation. In addition to the genotypic effects, the growing year influences GL degradation as well. An untargeted metabolomics approach revealed that 23 out of 413 detected metabolites were associated with GL thermal degradation rate constants. Three of them could be identified asflavonols and two as glucosinolates. QTL for two flavonols co-localize with the QTL for GLs degradation. Conclusions The research conducted in this thesis demonstrates that GL thermal degradation is partly genetically regulated. Furthermore, environmental factors, such as season and growing year, influence GL thermal degradation. The findings provide the methodology to breed for vegetables with increased GL retention during food processing. More studies are required to test the stability of the identified QTL in different environments and growing years to apply GL retention as breeding trait. Furthermore, one method was shown towards the identification of metabolic factors causing the variation of GL thermal degradation in different vegetables, which also requires future research to confirm these findings. In order to improve specific quality attributes of plant-based foods, breeding for quantitative food processing traits is a promising and challenging approach. It has potential to improve the nutritional quality of food products by combining the disciplines food and plant science to select and breed for varieties with not only higher initial amounts of phytochemicals but also with a high retention during processing.

In this thesis the metabolic variation in Brassica rapa is described based on results of metabolic profiling of a core collection of 168 accessions representing the different crop types and geographical origin and a Doubled Haploid population. In Chapter 2 we describe the genetic and phenotypic variation of this core collection to explore the possibility of following association mapping methods to identify genes involved in metabolic regulation. We explored through a genome wide and candidate gene approach different association mapping methods in a core collection in Chapters 3 and 4 respectively and in Chapter 5 we combined the QTL analysis of targeted and untargeted metabolites profiled through LC-MS with expression QTLs following a genetical genomics approach aiming to detect genes underlying the metabolite QTL. The genetic diversity evaluated through the screening of AFLP and SSR markers was correlated with classification of accessions using morphological and metabolic trait values. The relationship between accessions in groups was compared using hierarchical clustering and the STRUCTURE program. Using Random Forests classification a set of metabolites was selected that differentiated the different sub groups as determined by STRUCTURE (Chapter 2). Based on the classification into subpopulations using the STRUCTURE program we included the subpopulations as a correction term in our statistical model for association studies (Chapter 3). Additionally, because of the increasing amount of data that will be soon available through sequencing technology we tested the use of Random Forests in the search for marker-trait association for the isoprenoids pathway. Using the results obtained with the linear models as implemented in TASSEL and the results obtained in Random Forests we found a set of 16 significant markers with potential use for marker assisted selection in breeding for several isoprenoidsThe determination of map positions through synteny prediction and genetic mapping of a group of genes from the glucosinolate pathway lead us to identify Myb28 and MAM as candidate genes mapping under a previously detected major QTL for glucosinolates We followed an association mapping approach to investigate their role in the variation in glucosinolates in the core collection by profiling 37 SSR markers, which included markers linked to these candidate genes and markers distributed along different positions in linkage group A03 (Chapter 4). Interestingly, not only MAM and Myb28, but the AOP and GS-OH genes involved in side chain modification and Myb29 in transcriptional regulation were also associated with glucosinolate levels. A genetical genomics approach was followed to identify candidate genes for variation inmetabolites of six biosynthetic pathways: carotenoids, tocopherols, folates, glucosinolates, flavonoids and phenylpropanoids, based on the co-localization analysis and comparison between metabolic (m)QTLs and expression (e)QTLs (Chapter 5). A Doubled Haploid (DH) population was profiled for metabolite content and variation through targeted and LC-MS untargeted approaches. Additionally, the same population was profiled for transcript variation with a newly developed 105K Cogenics array assembled using mainly EST sequences from three species: B. napus, B. rapa and B. oleracea. Co-localization of eQTLs and mQTLs for several isoprenoids (tocopherols and carotenoids) and glucosinolates lead us to the identification of candidate genes for these pathways. However, further work is needed to identify the gene or genes underlying a major cluster of QTLs for 112 centrotypes derived from the LC-MS untargeted data. The results obtained through this combined approach and considerations that need to be taken into account when performing these types of studies with regard to identification of paralogues and the use of a multi Brassica species microarray for transcript profiling in Brassica rapa are discussed.In the final Chapter, the combined use of core collections encompassing the genetic diversity within B. rapa and biparental DH populations to unravel the genetic regulation of the metabolome are discussed.

In this thesis molecular genetic studies on Brassica rapa are described based on a collection of 256 accessions and 6 segregating populations. In chapter 2 and 3 the genetic variation and population structure are characterized in a set of genotypes from different geographical origins representing the various cultivar types. The association of traits with AFLP markers is analyzed in chapter 3, and the development of various mapping populations, linkage map construction and QTL analysis of phytate and diverse morphological traits are described in chapter 4 and 5.Genetic diversity in the primary gene pool of B. rapa was assessed by AFLP fingerprinting (chapter 2). The relationship between accessions was revealed by the dendrogram,indicating thatdifferent cultivar groups are often region(East Asia vs.Europe)specific, emerging independently in the different geographic regions. The UPGMA dendrogram (chapter 2) and population structure (chapter 3) showed that grouping based on markers coincided often with morphotypes (cultivar groups) within a geographic region. However this clustering was not supported by significant bootstrap values, suggesting that only a few genes are involved in causing the large differences in morphologies.A number of markers differed between subpopulations thereby providing an example oflinkage disequilibrium (LD) due to population structure.Diversity collections can be used to survey the allele frequencies and to explore associations with traits (chapter 3). The STRUCTURE program indicated an association between population structure and trait values even for traits such as phytate and phosphate levels.The population structureshould therefore be considered in association mapping studies in B. rapa .Markers that show association after correction for substructure can reliably be interpreted as being linked. Using the Composite Interval association mapping procedure, 54 markers were found significantly associated with at least one of the 9 different traits that were analyzed, 16 of which had known map positions. The observation that some of the marker-trait associations were confirmed by QTL analysis indicated that association mapping allows the detection of linkage with moderately frequent alleles.A multiple population approach was applied in QTL analysis for phytateandmorphologicaltraits, in which the populations were developed from wide crosses and alleles of multiple parental accessions can be evaluated,revealing a large number of genomic regions harboring allelic variation for traits of interest. For phytate and phosphate contents in seeds and leaves, and 20 morphological traits involved in flowering time, seed traits, plant height, leaf traits and turnip formation we identified a total of 54 QTL positions. Co-location of QTL for different traits was found in many cases, which might suggest pleiotropy or tight linkage. The analysis of co-location of QTL for phytate/phosphate and parental allelic effects suggested that these QTL control total phosphorus levels or are specific for the phytate pathway in B. rapa. Principal component analysis and co-localization of QTL for morphological traits indicated that some components of the genetic control of certain leaf and seed-related traits, flowering time and turnip formation might be based on the same genes, indicating a commongenetic regulation of correlated traits underlying these QTL.The comparative analyses of QTL for certain traits, such as phytate and phosphate contents and flowering time, between the 6 populations and with Arabidopsis thaliana or other related Brassica species are discussed.

Powdery mildew ( Oidium neolycopersici) is a worldwide obligate fungal disease of tomato ( Solanum lycopersicum ). Six monogenic Ol genes and three major QTLs were identified and mapped on tomato genome. In this thesis, the mechanisms of both compatible and incompatible interactions of tomato and O. neolycopersici were investigated at transcriptional, microscopic and macroscopic levels. The monogenic resistance responses mediated by papilla formation, fast and slow hypersensitive response (HR) displayed different transcript profiles and could employed different defense pathways. The polygenic resistance mediated by QTLs is mainly associated with slow HR and penetrated papilla. Although the individual QTLs are additive to each other the pyramiding of QTLs only alters the defense pathways quantitatively rather than qualitatively. During the compatible and slow-HR mediated incompatible interactions tomato plants employ similar genes and the timing difference in the expression of these genes are crucial to the final fate of the interactions.

Oidium neolycopersiciis the causal agent of the tomato powdery mildew disease. Besides a few recently released resistant cultivars, all tomato cultivars are susceptible to O. neolycopersici. Therefore, resistance to O. neolycopersici is an important trait in tomato breeding.The aim of this research is to study theinteraction between tomato ( Lycopersicon esculentum ) and tomato powdery mildew ( O. neolycopersici ). Firstly, we characterized the genetic basis for several resistances against O. neolycopersicioriginating from wild Lycopersicon species and mapped the correspondingresistance genes on the tomato genome. Remarkably, all the mapped dominant Ol -genes are located in three loci on tomato Chromosome 6. On the long arm, one locus contains the resistance genes Ol-1 and Ol-3 , originating from L. hirsutum G1.1560 and G1.1290, respectively, while another closely linked locus harbors Ol-5 , a resistance gene originating from L.hirsutum PI247087. On the short arm of Chromosome 6, one locus contains the two resistance genes Ol-4 (originating from L. peruvianum LA2172) and Ol-6 (unknown origin). In addition to these Ol -loci, three quantitative trait loci (QTLs) have been identified governing the O. neolycopersici resistance in L. parviflorum G1. 1601. One QTL ( Ol-qtl1 ) interval overlaps with Ol-1 , Ol-3 and Ol-5 . Two other QTLs ( Ol-qtl2 and Ol-qtl3 ) are linked on Chromosome 12 with Ol-qtl2 in the vicinity of the Lv locus that confers resistance to another powdery mildew species, Leveillula taurica . Secondly, we generated a set of near isogenic lines (NILs), each of which contains an individual Ol -gene in a genetic background of L.esculentum cv. Moneymaker. These NILs represent well-defined plant material and are a very useful tool to study the interaction between Ol -genes and O. neolycopersici isolates. Thirdly, we determined the race-specificity of the resistance conferred by the Ol -genes by testing the NILs with local isolates of O.neolycopersici in different geographic places. In addition to the dominant Ol -genes, the recessive gene ol-2 that originates from L. esculentum var cerasiforme and is located on Chromosome 4 (Ciccarese et al., 1998; De Giovanni et al., 2004) was also included in our study. Our data suggested that the resistance to O. neolycopersici conferred by different Ol -genes ( Ol-1, ol-2, Ol-3, Ol-4, Ol-5 and Ol-6 ) can be race-specific. Finally, we studied the resistance mechanisms associated with different Ol -genes by using the NILs. Microscopically, the resistance conferred by the dominant Ol -genes is associated with a hypersensitive reaction (HR), while, the resistance governed by the recessive gene ol-2 is related to papilla formation.