Genetic diversity of tomato response to heat stress at the QTL and transcriptome levels.

Tomato is a widely cultivated crop, which can grow in many environments. However, temperature above 30°C impairs its reproduction, subsequently impacting fruit yield. We assessed the impact of high-temperature stress (HS) in two tomato experimental populations, a multi-parental advanced generation intercross (MAGIC) population and a core-collection (CC) of small-fruited tomato accessions. Both populations were evaluated for 11 traits related to yield components, phenology and fruit quality in optimal and HS conditions. HS significantly impacted all traits in both populations, but a few genotypes with stable yield under HS were identified. A plasticity index was computed for each individual to measure the extent of the heat impact for each trait. Quantitative trait loci (QTL) were detected in control and HS conditions as well as for plasticity index. Linkage and genome-wide association analyses in the MAGIC and CC populations identified a total of 98 and 166 QTLs, respectively. Taking the two populations together, 69 plasticity QTLs (pQTLs) were involved in tomato heat response for 11 traits. The transcriptome changes in the ovary of six genotypes with contrasted responses to HS were studied, and 837 genes differentially expressed according to the conditions were detected. Combined with previous transcriptome studies, these results were used to propose candidate genes for HS response QTLs.

Inheritance of Secondary Metabolites and Gene Expression Related to Tomato Fruit Quality.

Flavour and nutritional quality are important goals for tomato breeders. This study aimed to shed light upon transgressive behaviors for fruit metabolic content. We studied the metabolic contents of 44 volatile organic compounds (VOCs), 18 polyphenolics, together with transcriptome profiles in a factorial design comprising six parental lines and their 14 F1 hybrids (HF1) among which were five pairs of reciprocal HF1. After cluster analyses of the metabolome dataset and co-expression network construction of the transcriptome dataset, we characterized the mode of inheritance of each component. Both overall and per-cross mode of inheritance analyses revealed as many additive and non-additive modes of inheritance with few reciprocal effects. Up to 66% of metabolites displayed transgressions in a HF1 relative to parental values. Analysis of the modes of inheritance of metabolites revealed that: (i) transgressions were mostly of a single type whichever the cross and poorly correlated to the genetic distance between parental lines; (ii) modes of inheritance were scarcely consistent between the 14 crosses but metabolites belonging to the same cluster displayed similar modes of inheritance for a given cross. Integrating metabolome, transcriptome and modes of inheritance analyses suggested a few candidate genes that may drive important changes in fruit VOC contents.

Genetic basis of phenotypic plasticity and genotype × environment interactions in a multi-parental tomato population.

Deciphering the genetic basis of phenotypic plasticity and genotype × environment interactions (G×E) is of primary importance for plant breeding in the context of global climate change. Tomato (Solanum lycopersicum) is a widely cultivated crop that can grow in different geographical habitats and that displays a great capacity for expressing phenotypic plasticity. We used a multi-parental advanced generation intercross (MAGIC) tomato population to explore G×E and plasticity for multiple traits measured in a multi-environment trial (MET) comprising optimal cultural conditions together with water deficit, salinity, and heat stress over 12 environments. Substantial G×E was observed for all the traits measured. Different plasticity parameters were estimated by employing Finlay-Wilkinson and factorial regression models and these were used together with genotypic means for quantitative trait loci (QTL) mapping analyses. In addition, mixed linear models were also used to investigate the presence of QTL × environment interactions. The results highlighted a complex genetic architecture of tomato plasticity and G×E. Candidate genes that might be involved in the occurrence of G×E are proposed, paving the way for functional characterization of stress response genes in tomato and for breeding climate-adapted cultivars.

Allele-specific expression and genetic determinants of transcriptomic variations in response to mild water deficit in tomato.

Characterizing the natural diversity of gene expression across environments is an important step in understanding how genotype-by-environment interactions shape phenotypes. Here, we analyzed the impact of water deficit onto gene expression levels in tomato at the genome-wide scale. We sequenced the transcriptome of growing leaves and fruit pericarps at cell expansion stage in a cherry and a large fruited accession and their F1 hybrid grown under two watering regimes. Gene expression levels were steadily affected by the genotype and the watering regime. Whereas phenotypes showed mostly additive inheritance, ~80% of the genes displayed non-additive inheritance. By comparing allele-specific expression (ASE) in the F1 hybrid to the allelic expression in both parental lines, respectively, 3005 genes in leaf and 2857 genes in fruit deviated from 1:1 ratio independently of the watering regime. Among these genes, ~55% were controlled by cis factors, ~25% by trans factors and ~20% by a combination of both types of factors. A total of 328 genes in leaf and 113 in fruit exhibited significant ASE-by-watering regime interaction, among which ~80% presented trans-by-watering regime interaction, suggesting a response to water deficit mediated through a majority of trans-acting loci in tomato. We cross-validated the expression levels of 274 transcripts in fruit and leaves of 124 recombinant inbred lines (RILs) and identified 163 expression quantitative trait loci (eQTLs) mostly confirming the divergences identified by ASE. Combining phenotypic and expression data, we observed a complex network of variation between genes encoding enzymes involved in the sugar metabolism.

Genotype by watering regime interaction in cultivated tomato: lessons from linkage mapping and gene expression.

KEY MESSAGE: In tomato, genotype by watering interaction resulted from genotype re-ranking more than scale changes. Interactive QTLs according to watering regime were detected. Differentially expressed genes were identified in some intervals. ABSTRACT: As a result of climate change, drought will increasingly limit crop production in the future. Studying genotype by watering regime interactions is necessary to improve plant adaptation to low water availability. In cultivated tomato (Solanum lycopersicum L.), extensively grown in dry areas, well-mastered water deficits can stimulate metabolite production, increasing plant defenses and concentration of compounds involved in fruit quality, at the same time. However, few tomato Quantitative Trait Loci (QTLs) and genes involved in response to drought are identified or only in wild species. In this study, we phenotyped a population of 119 recombinant inbred lines derived from a cross between a cherry tomato and a large fruit tomato, grown in greenhouse under two watering regimes, in two locations. A large genetic variability was measured for 19 plant and fruit traits, under the two watering treatments. Highly significant genotype by watering regime interactions were detected and resulted from re-ranking more than scale changes. The population was genotyped for 679 SNP markers to develop a genetic map. In total, 56 QTLs were identified among which 11 were interactive between watering regimes. These later mainly exhibited antagonist effects according to watering treatment. Variation in gene expression in leaves of parental accessions revealed 2259 differentially expressed genes, among which candidate genes presenting sequence polymorphisms were identified under two main interactive QTLs. Our results provide knowledge about the genetic control of genotype by watering regime interactions in cultivated tomato and the possible use of deficit irrigation to improve tomato quality.

Genetic control of tomato fruit quality: from QTL mapping to Genome Wide Association studies and breeding.

Consumers began to complain about the taste of tomato varieties in the late 1990's. Although tomato taste is influenced by environmental and post-harvest conditions, varieties show a large diversity for fruit quality traits. We herein review our past and present research work intended to improve tomato fruit quality. First, results from sensory analysis allowed identifying important traits for consumer preferences. Then, we dissected the genetic control of flavor related traits by mapping several QTL in the last 20 years, and identified the genes corresponding to a few major QTL. Since the availability of the tomato genome sequence, genome-wide association studies were performed on several panels of tomato accessions. We discovered a large number of associations for fruit composition and identified relevant allele combinations for breeding. We then performed a meta-analysis combining the results of several studies. We also checked the inheritance of quality traits at the hybrid level and assessed how genomic prediction could help selecting better tomato varieties.

Les consommateurs ont commencé à se plaindre du goût des variétés de tomates à la fin des années 1990. Bien que le goût de la tomate soit influencé par les conditions de culture et de post-récolte, les variétés présentent une grande diversité pour les caractéristiques de qualité des fruits. Nous passons ici en revue nos travaux de recherche passés et présents destinés à comprendre la diversité génétique et améliorer la qualité des fruits de tomate. Les résultats d'analyses sensorielles ont tout d'abord permis d'identifier les traits importants pour les préférences des consommateurs. Ensuite, nous avons disséqué le contrôle génétique des caractères liés à ces traits, cartographié de nombreux QTL depuis 20 ans et identifié les gènes correspondant à quelques QTL majeurs. Depuis la disponibilité de la séquence du génome de la tomate, des études d'association à l'échelle du génome ont été réalisées sur plusieurs panels d'accessions de tomate. Nous avons découvert un grand nombre d'associations pour la composition des fruits, et identifié les combinaisons d'allèles pertinentes pour la sélection. Nous avons ensuite réalisé une méta-analyse combinant les résultats de plusieurs études. Nous avons également vérifié l'hérédité des caractères de qualité au niveau hybride, et évalué comment la prédiction génomique pourrait aider à sélectionner de meilleures variétés de tomates.

Genetic Variability in Seed Longevity and Germination Traits in a Tomato MAGIC Population in Contrasting Environments.

The stable production of high vigorous seeds is pivotal to crop yield. Also, a high longevity is essential to avoid progressive loss of seed vigour during storage. Both seed traits are strongly influenced by the environment during seed development. Here, we investigated the impact of heat stress (HS) during fruit ripening on tomato seed lifespan during storage at moderate relative humidity, speed (t50) and homogeneity of germination, using a MAGIC population that was produced under optimal and HS conditions. A plasticity index was used to assess the extent of the impact of HS for each trait. HS reduced the average longevity and germination homogeneity by 50% within the parents and MAGIC population. However, there was a high genetic variability in the seed response to heat stress. A total of 39 QTLs were identified, including six longevity QTLs for seeds from control (3) and HS (3) conditions, and six plasticity QTLs for longevity, with only one overlapping with a longevity QTL under HS. Four out of the six longevity QTL co-located with t50 QTL, revealing hotspots for seed quality traits. Twenty-one QTLs with intervals below 3 cM were analyzed using previous transcriptome and gene network data to propose candidate genes for seed vigour and longevity traits.

EDS1 contributes to nonhost resistance of Arabidopsis thaliana against Erwinia amylovora.

Erwinia amylovora causes fire blight in rosaceous plants. In nonhost Arabidopsis thaliana, E. amylovora triggers necrotic symptoms associated with transient bacterial multiplication, suggesting either that A. thaliana lacks a susceptibility factor or that it actively restricts E. amylovora growth. Inhibiting plant protein synthesis at the time of infection led to an increase in necrosis and bacterial multiplication and reduced callose deposition, indicating that A. thaliana requires active protein synthesis to restrict E. amylovora growth. Analysis of the callose synthase-deficient pmr4-1 mutant indicated that lack of callose deposition alone did not lead to increased sensitivity to E. amylovora. Transcriptome analysis revealed that approximately 20% of the genes induced following E. amylovora infection are related to defense and signaling. Analysis of mutants affected in NDR1 and EDS1, two main components of the defense-gene activation observed, revealed that E. amylovora multiplied ten times more in the eds1-2 mutant than in the wild type but not in the ndr1-1 mutant. Analysis of mutants affected in three WRKY transcription factors showing EDS1-dependent activation identified WRKY46 and WRKY54 as positive regulators and WRKY70 as a negative regulator of defense against E. amylovora. Altogether, we show that EDS1 is a positive regulator of nonhost resistance against E. amylovora in A. thaliana and hypothesize that it controls the production of several effective defenses against E. amylovora through the action of WRKY46 and WRKY54, while WRKY70 acts as a negative regulator.

Multiple haplotype-based analyses provide genetic and evolutionary insights into tomato fruit weight and composition.

Improving fruit quality traits such as metabolic composition remains a challenge for tomato breeders. To better understand the genetic architecture of these traits and decipher the demographic history of the loci controlling tomato quality traits, we applied an innovative approach using multiple haplotype-based analyses, aiming to test the potentials of haplotype based study in association and genomic prediction studies. We performed and compared haplotype vs SNP-based associations (hapQTL) with multi-locus mixed model (MLMM), focusing on tomato fruit weight and metabolite contents (i.e. sugars, organic acids and amino acids). Using a panel of 163 tomato accessions genotyped with 5995 SNPs, we detected a total of 784 haplotype blocks, with an average size of haplotype blocks ~58 kb. A total of 108 significant associations for 26 traits were detected thanks to Haplotype/SNP-based Bayes models. Haplotype-based Bayes model (97 associations) outperformed SNP-based Bayes model (50 associations) and MLMM (53 associations) in identifying marker-trait associations as well as in genomic prediction (especially for those traits with moderate to low heritability). To decipher the demographic history, we identified 24 positive selective sweeps using the integrated haplotype score (iHS). Most of the significant associations for tomato quality traits were located within selective sweeps (54.63% and 71.7% in hapQTL and MLMM models, respectively). Promising candidate genes were identified controlling tomato fruit weight and metabolite contents. We thus demonstrated the benefits of using haplotypes for evolutionary and genetic studies, providing novel insights into tomato quality improvement and breeding history.

Analysis of BAC end sequences in oak, a keystone forest tree species, providing insight into the composition of its genome.

BACKGROUND: One of the key goals of oak genomics research is to identify genes of adaptive significance. This information may help to improve the conservation of adaptive genetic variation and the management of forests to increase their health and productivity. Deep-coverage large-insert genomic libraries are a crucial tool for attaining this objective. We report herein the construction of a BAC library for Quercus robur, its characterization and an analysis of BAC end sequences. RESULTS: The EcoRI library generated consisted of 92,160 clones, 7% of which had no insert. Levels of chloroplast and mitochondrial contamination were below 3% and 1%, respectively. Mean clone insert size was estimated at 135 kb. The library represents 12 haploid genome equivalents and, the likelihood of finding a particular oak sequence of interest is greater than 99%. Genome coverage was confirmed by PCR screening of the library with 60 unique genetic loci sampled from the genetic linkage map. In total, about 20,000 high-quality BAC end sequences (BESs) were generated by sequencing 15,000 clones. Roughly 5.88% of the combined BAC end sequence length corresponded to known retroelements while ab initio repeat detection methods identified 41 additional repeats. Collectively, characterized and novel repeats account for roughly 8.94% of the genome. Further analysis of the BESs revealed 1,823 putative genes suggesting at least 29,340 genes in the oak genome. BESs were aligned with the genome sequences of Arabidopsis thaliana, Vitis vinifera and Populus trichocarpa. One putative collinear microsyntenic region encoding an alcohol acyl transferase protein was observed between oak and chromosome 2 of V. vinifera. CONCLUSIONS: This BAC library provides a new resource for genomic studies, including SSR marker development, physical mapping, comparative genomics and genome sequencing. BES analysis provided insight into the structure of the oak genome. These sequences will be used in the assembly of a future genome sequence for oak.

Breeding Tomato Hybrids for Flavour: Comparison of GWAS Results Obtained on Lines and F1 Hybrids.

Tomato flavour is an important goal for breeders. Volatile organic compounds (VOCs) are major determinants of tomato flavour. Although most tomato varieties for fresh market are F1 hybrids, most studies on the genetic control of flavour-related traits are performed on lines. We quantified 46 VOCs in a panel of 121 small fruited lines and in a test cross panel of 165 hybrids (the previous panel plus 44 elite cherry tomato lines crossed with a common line). High and consistent heritabilities were assessed for most VOCs in the two panels, and 65% of VOC contents were strongly correlated between lines and hybrids. Additivity was observed for most VOCs. We performed genome wide association studies (GWAS) on the two panels separately, along with a third GWAS on the test cross subset carrying only F1 hybrids corresponding to the line panel. We identified 205, 183 and 138 associations, respectively. We identified numerous overlapping associations for VOCs belonging to the same metabolic pathway within each panel; we focused on seven chromosome regions with clusters of associations simultaneously involved in several key VOCs for tomato aroma. The study highlighted the benefit of testcross panels to create tasty F1 hybrid varieties.

Brain transcriptional stability upon prion protein-encoding gene invalidation in zygotic or adult mouse.

BACKGROUND: The physiological function of the prion protein remains largely elusive while its key role in prion infection has been expansively documented. To potentially assess this conundrum, we performed a comparative transcriptomic analysis of the brain of wild-type mice with that of transgenic mice invalidated at this locus either at the zygotic or at the adult stages. RESULTS: Only subtle transcriptomic differences resulting from the Prnp knockout could be evidenced, beside Prnp itself, in the analyzed adult brains following microarray analysis of 24 109 mouse genes and QPCR assessment of some of the putatively marginally modulated loci. When performed at the adult stage, neuronal Prnp disruption appeared to sequentially induce a response to an oxidative stress and a remodeling of the nervous system. However, these events involved only a limited number of genes, expression levels of which were only slightly modified and not always confirmed by RT-qPCR. If not, the qPCR obtained data suggested even less pronounced differences. CONCLUSIONS: These results suggest that the physiological function of PrP is redundant at the adult stage or important for only a small subset of the brain cell population under classical breeding conditions. Following its early reported embryonic developmental regulation, this lack of response could also imply that PrP has a more detrimental role during mouse embryogenesis and that potential transient compensatory mechanisms have to be searched for at the time this locus becomes transcriptionally activated.

CATdb: a public access to Arabidopsis transcriptome data from the URGV-CATMA platform.

CATdb is a free resource available at http://urgv.evry.inra.fr/CATdb that provides public access to a large collection of transcriptome data for Arabidopsis thaliana produced by a single Complete Arabidopsis Transcriptome Micro Array (CATMA) platform. CATMA probes consist of gene-specific sequence tags (GSTs) of 150-500 bp. The v2 version of CATMA contains 24 576 GST probes representing most of the predicted A. thaliana genes, and 615 probes tiling the chloroplastic and mitochondrial genomes. Data in CATdb are entirely processed with the same standardized protocol, from microarray printing to data analyses. CATdb contains the results of 53 projects including 1724 hybridized samples distributed between 13 different organs, 49 different developmental conditions, 45 mutants and 63 environmental conditions. All the data contained in CATdb can be downloaded from the web site and subsets of data can be sorted out and displayed either by keywords, by experiments, genes or lists of genes up to 100. CATdb gives an easy access to the complete description of experiments with a picture of the experiment design.

Integration of QTL, Transcriptome and Polymorphism Studies Reveals Candidate Genes for Water Stress Response in Tomato.

Water deficit (WD) leads to significant phenotypic changes in crops resulting from complex stress regulation mechanisms involving responses at the physiological, biochemical and molecular levels. Tomato growth and fruit quality have been shown to be significantly affected by WD stress. Understanding the molecular mechanism underlying response to WD is crucial to develop tomato cultivars with relatively high performance under low watering conditions. Transcriptome response to WD was investigated through the RNA sequencing of fruit and leaves in eight accessions grown under two irrigation conditions, in order to get insight into the complex genetic regulation of WD response in tomato. Significant differences in genotype WD response were first observed at the phenotypic level for fruit composition and plant development traits. At the transcriptome level, a total of 14,065 differentially expressed genes (DEGs) in response to WD were detected, among which 7393 (53%) and 11,059 (79%) were genotype- and organ-specific, respectively. Water deficit induced transcriptome variations much stronger in leaves than in fruit. A significant effect of the genetic background on expression variation was observed compared to the WD effect, along with the presence of a set of genes showing a significant genotype x watering regime interaction. Integrating the DEGs with previously identified WD response quantitative trait loci (QTLs) mapped in a multi-parental population derived from the crossing of the eight genotypes narrowed the candidate gene lists to within the confidence intervals surrounding the QTLs. The results present valuable resources for further study to decipher the genetic determinants of tomato response to WD.

Genome-scale Arabidopsis promoter array identifies targets of the histone acetyltransferase GCN5.

We have assembled approximately 20 000 Arabidopsis thaliana promoter regions, compatible with functional studies that require cloning and with microarray applications. The promoter fragments can be captured as modular entry clones (MultiSite Gateway format) via site-specific recombinational cloning, and transferred into vectors of choice to investigate transcriptional networks. The fragments can also be amplified by PCR and printed on glass arrays. In combination with immunoprecipitation of protein-DNA complexes (ChIP-chip), these arrays enable characterization of binding sites for chromatin-associated proteins or the extent of chromatin modifications at genome scale. The Arabidopsis histone acetyltransferase GCN5 associated with 40% of the tested promoters. At most sites, binding did not depend on the integrity of the GCN5 bromodomain. However, the presence of the bromodomain was necessary for binding to 11% of the promoter regions, and correlated with acetylation of lysine 14 of histone H3 in these promoters. Combined analysis of ChIP-chip and transcriptomic data indicated that binding of GCN5 does not strictly correlate with gene activation. GCN5 has previously been shown to be required for light-regulated gene expression and growth, and we found that GCN5 targets were enriched in early light-responsive genes. Thus, in addition to its transcriptional activation function, GCN5 may play an important role in priming activation of inducible genes under non-induced conditions.

Meta-analysis of genome-wide association studies provides insights into genetic control of tomato flavor.

Tomato flavor has changed over the course of long-term domestication and intensive breeding. To understand the genetic control of flavor, we report the meta-analysis of genome-wide association studies (GWAS) using 775 tomato accessions and 2,316,117 SNPs from three GWAS panels. We discover 305 significant associations for the contents of sugars, acids, amino acids, and flavor-related volatiles. We demonstrate that fruit citrate and malate contents have been impacted by selection during domestication and improvement, while sugar content has undergone less stringent selection. We suggest that it may be possible to significantly increase volatiles that positively contribute to consumer preferences while reducing unpleasant volatiles, by selection of the relevant allele combinations. Our results provide genetic insights into the influence of human selection on tomato flavor and demonstrate the benefits obtained from meta-analysis.

Water Deficit and Salinity Stress Reveal Many Specific QTL for Plant Growth and Fruit Quality Traits in Tomato.

Quality is a key trait in plant breeding, especially for fruit and vegetables. Quality involves several polygenic components, often influenced by environmental conditions with variable levels of genotype × environment interaction that must be considered in breeding strategies aiming to improve quality. In order to assess the impact of water deficit and salinity on tomato fruit quality, we evaluated a multi-parent advanced generation intercross (MAGIC) tomato population in contrasted environmental conditions over 2 years, one year in control vs. drought condition and the other in control vs. salt condition. Overall 250 individual lines from the MAGIC population-derived from eight parental lines covering a large diversity in cultivated tomato-were used to identify QTL in both experiments for fruit quality and yield component traits (fruit weight, number of fruit, Soluble Solid Content, firmness), phenology traits (time to flower and ripe) and a vegetative trait, leaf length. All the traits showed a large genotype variation (33-86% of total phenotypic variation) in both experiments and high heritability whatever the year or treatment. Significant genotype × treatment interactions were detected for five of the seven traits over the 2 years of experiments. QTL were mapped using 1,345 SNP markers. A total of 54 QTL were found among which 15 revealed genotype × environment interactions and 65% (35 QTL) were treatment specific. Confidence intervals of the QTL were projected on the genome physical map and allowed identifying regions carrying QTL co-localizations, suggesting pleiotropic regulation. We then applied a strategy for candidate gene detection based on the high resolution mapping offered by the MAGIC population, the allelic effect of each parental line at the QTL and the sequence information of the eight parental lines.

Analysis of CATMA transcriptome data identifies hundreds of novel functional genes and improves gene models in the Arabidopsis genome.

BACKGROUND: Since the finishing of the sequencing of the Arabidopsis thaliana genome, the Arabidopsis community and the annotator centers have been working on the improvement of gene annotation at the structural and functional levels. In this context, we have used the large CATMA resource on the Arabidopsis transcriptome to search for genes missed by different annotation processes. Probes on the CATMA microarrays are specific gene sequence tags (GSTs) based on the CDS models predicted by the Eugene software. Among the 24 576 CATMA v2 GSTs, 677 are in regions considered as intergenic by the TAIR annotation. We analyzed the cognate transcriptome data in the CATMA resource and carried out data-mining to characterize novel genes and improve gene models. RESULTS: The statistical analysis of the results of more than 500 hybridized samples distributed among 12 organs provides an experimental validation for 465 novel genes. The hybridization evidence was confirmed by RT-PCR approaches for 88% of the 465 novel genes. Comparisons with the current annotation show that these novel genes often encode small proteins, with an average size of 137 aa. Our approach has also led to the improvement of pre-existing gene models through both the extension of 16 CDS and the identification of 13 gene models erroneously constituted of two merged CDS. CONCLUSION: This work is a noticeable step forward in the improvement of the Arabidopsis genome annotation. We increased the number of Arabidopsis validated genes by 465 novel transcribed genes to which we associated several functional annotations such as expression profiles, sequence conservation in plants, cognate transcripts and protein motifs.

Dissecting quantitative trait variation in the resequencing era: complementarity of bi-parental, multi-parental and association panels.

Quantitative trait loci (QTL) have been identified using traditional linkage mapping and positional cloning identified several QTLs. However linkage mapping is limited to the analysis of traits differing between two lines and the impact of the genetic background on QTL effect has been underlined. Genome-wide association studies (GWAs) were proposed to circumvent these limitations. In tomato, we have shown that GWAs is possible, using the admixed nature of cherry tomato genomes that reduces the impact of population structure. Nevertheless, GWAs success might be limited due to the low decay of linkage disequilibrium, which varies along the genome in this species. Multi-parent advanced generation intercross (MAGIC) populations offer an alternative to traditional linkage and GWAs by increasing the precision of QTL mapping. We have developed a MAGIC population by crossing eight tomato lines whose genomes were resequenced. We showed the potential of the MAGIC population when coupled with whole genome sequencing to detect candidate single nucleotide polymorphisms (SNPs) underlying the QTLs. QTLs for fruit quality traits were mapped and related to the variations detected at the genome sequence and expression levels. The advantages and limitations of the three types of population, in the context of the available genome sequence and resequencing facilities, are discussed.

Spotting effect in microarray experiments.

BACKGROUND: Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects data obtained with Cy3/Cy5 spotted glass arrays. It yields a periodic pattern altering both signal (Cy3/Cy5 ratio) and intensity across the array. RESULTS: Using the variogram, a geostatistical tool, we characterized the observed variability, called here the spotting effect because it most probably arises during steps in the array printing procedure. CONCLUSIONS: The spotting effect is not appropriately corrected by current normalization methods, even by those addressing spatial variability. Importantly, the spotting effect may alter differential and clustering analysis.