End-to-end multimodal 3D imaging and machine learning workflow for non-destructive phenotyping of grapevine trunk internal structure.

Quantifying healthy and degraded inner tissues in plants is of great interest in agronomy, for example, to assess plant health and quality and monitor physiological traits or diseases. However, detecting functional and degraded plant tissues in-vivo without harming the plant is extremely challenging. New solutions are needed in ligneous and perennial species, for which the sustainability of plantations is crucial. To tackle this challenge, we developed a novel approach based on multimodal 3D imaging and artificial intelligence-based image processing that allowed a non-destructive diagnosis of inner tissues in living plants. The method was successfully applied to the grapevine (Vitis vinifera L.). Vineyard's sustainability is threatened by trunk diseases, while the sanitary status of vines cannot be ascertained without injuring the plants. By combining MRI and X-ray CT 3D imaging with an automatic voxel classification, we could discriminate intact, degraded, and white rot tissues with a mean global accuracy of over 91%. Each imaging modality contribution to tissue detection was evaluated, and we identified quantitative structural and physiological markers characterizing wood degradation steps. The combined study of inner tissue distribution versus external foliar symptom history demonstrated that white rot and intact tissue contents are key-measurements in evaluating vines' sanitary status. We finally proposed a model for an accurate trunk disease diagnosis in grapevine. This work opens new routes for precision agriculture and in-situ monitoring of tissue quality and plant health across plant species.

Enhancing grapevine breeding efficiency through genomic prediction and selection index.

Grapevine (Vitis vinifera) breeding reaches a critical point. New cultivars are released every year with resistance to powdery and downy mildews. However, the traditional process remains time-consuming, taking 20-25 years, and demands the evaluation of new traits to enhance grapevine adaptation to climate change. Until now, the selection process has relied on phenotypic data and a limited number of molecular markers for simple genetic traits such as resistance to pathogens, without a clearly defined ideotype, and was carried out on a large scale. To accelerate the breeding process and address these challenges, we investigated the use of genomic prediction, a methodology using molecular markers to predict genotypic values. In our study, we focused on 2 existing grapevine breeding programs: Rosé wine and Cognac production. In these programs, several families were created through crosses of emblematic and interspecific resistant varieties to powdery and downy mildews. Thirty traits were evaluated for each program, using 2 genomic prediction methods: Genomic Best Linear Unbiased Predictor and Least Absolute Shrinkage Selection Operator. The results revealed substantial variability in predictive abilities across traits, ranging from 0 to 0.9. These discrepancies could be attributed to factors such as trait heritability and trait characteristics. Moreover, we explored the potential of across-population genomic prediction by leveraging other grapevine populations as training sets. Integrating genomic prediction allowed us to identify superior individuals for each program, using multivariate selection index method. The ideotype for each breeding program was defined collaboratively with representatives from the wine-growing sector.

Interest of phenomic prediction as an alternative to genomic prediction in grapevine.

BACKGROUND: Phenomic prediction has been defined as an alternative to genomic prediction by using spectra instead of molecular markers. A reflectance spectrum provides information on the biochemical composition within a tissue, itself being under genetic determinism. Thus, a relationship matrix built from spectra could potentially capture genetic signal. This new methodology has been mainly applied in several annual crop species but little is known so far about its interest in perennial species. Besides, phenomic prediction has only been tested for a restricted set of traits, mainly related to yield or phenology. This study aims at applying phenomic prediction for the first time in grapevine, using spectra collected on two tissues and over two consecutive years, on two populations and for 15 traits, related to berry composition, phenology, morphological and vigour. A major novelty of this study was to collect spectra and phenotypes several years apart from each other. First, we characterized the genetic signal in spectra and under which condition it could be maximized, then phenomic predictive ability was compared to genomic predictive ability. RESULTS: For the first time, we showed that the similarity between spectra and genomic relationship matrices was stable across tissues or years, but variable across populations, with co-inertia around 0.3 and 0.6 for diversity panel and half-diallel populations, respectively. Applying a mixed model on spectra data increased phenomic predictive ability, while using spectra collected on wood or leaves from one year or another had less impact. Differences between populations were also observed for predictive ability of phenomic prediction, with an average of 0.27 for the diversity panel and 0.35 for the half-diallel. For both populations, a significant positive correlation was found across traits between predictive ability of genomic and phenomic predictions. CONCLUSION: NIRS is a new low-cost alternative to genotyping for predicting complex traits in perennial species such as grapevine. Having spectra and phenotypes from different years allowed us to exclude genotype-by-environment interactions and confirms that phenomic prediction can rely only on genetics.

A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs.

To cope with the challenges facing agriculture, speeding-up breeding programs is a worthy endeavor, especially for perennial species such as grapevine, but requires understanding the genetic architecture of target traits. To go beyond the mapping of quantitative trait loci in bi-parental crosses, we exploited a diversity panel of 279 Vitis vinifera L. cultivars planted in 5 blocks in the vineyard. This panel was phenotyped over several years for 127 traits including yield components, organic acids, aroma precursors, polyphenols, and a water stress indicator. The panel was genotyped for 63k single nucleotide polymorphisms by combining an 18K microarray and genotyping-by-sequencing. The experimental design allowed to reliably assess the genotypic values for most traits. Marker densification via genotyping-by-sequencing markedly increased the proportion of genetic variance explained by single nucleotide polymorphisms, and 2 multi-single nucleotide polymorphism models identified quantitative trait loci not found by a single nucleotide polymorphism-by-single nucleotide polymorphism model. Overall, 489 reliable quantitative trait loci were detected for 41% more response variables than by a single nucleotide polymorphism-by-single nucleotide polymorphism model with microarray-only single nucleotide polymorphisms, many new ones compared with the results from bi-parental crosses. A prediction accuracy higher than 0.42 was obtained for 50% of the response variables. Our overall approach as well as quantitative trait locus and prediction results provide insights into the genetic architecture of target traits. New candidate genes and the application into breeding are discussed.

Across-population genomic prediction in grapevine opens up promising prospects for breeding.

Crop breeding involves two selection steps: choosing progenitors and selecting individuals within progenies. Genomic prediction, based on genome-wide marker estimation of genetic values, could facilitate these steps. However, its potential usefulness in grapevine (Vitis vinifera L.) has only been evaluated in non-breeding contexts mainly through cross-validation within a single population. We tested across-population genomic prediction in a more realistic breeding configuration, from a diversity panel to ten bi-parental crosses connected within a half-diallel mating design. Prediction quality was evaluated over 15 traits of interest (related to yield, berry composition, phenology and vigour), for both the average genetic value of each cross (cross mean) and the genetic values of individuals within each cross (individual values). Genomic prediction in these conditions was found useful: for cross mean, average per-trait predictive ability was 0.6, while per-cross predictive ability was halved on average, but reached a maximum of 0.7. Mean predictive ability for individual values within crosses was 0.26, about half the within-half-diallel value taken as a reference. For some traits and/or crosses, these across-population predictive ability values are promising for implementing genomic selection in grapevine breeding. This study also provided key insights on variables affecting predictive ability. Per-cross predictive ability was well predicted by genetic distance between parents and when this predictive ability was below 0.6, it was improved by training set optimization. For individual values, predictive ability mostly depended on trait-related variables (magnitude of the cross effect and heritability). These results will greatly help designing grapevine breeding programs assisted by genomic prediction.

Characterization of genetic determinants of the resistance to phylloxera, Daktulosphaira vitifoliae, and the dagger nematode Xiphinema index from muscadine background.

BACKGROUND: Muscadine (Muscadinia rotundifolia) is known as a resistance source to many pests and diseases in grapevine. The genetics of its resistance to two major grapevine pests, the phylloxera D. vitifoliae and the dagger nematode X. index, vector of the Grapevine fanleaf virus (GFLV), was investigated in a backcross progeny between the F1 resistant hybrid material VRH8771 (Vitis-Muscadinia) derived from the muscadine R source 'NC184-4' and V. vinifera cv. 'Cabernet-Sauvignon' (CS). RESULTS: In this pseudo-testcross, parental maps were constructed using simple-sequence repeats markers and single nucleotide polymorphism markers from a GBS approach. For the VRH8771 map, 2271 SNP and 135 SSR markers were assembled, resulting in 19 linkage groups (LG) and an average distance between markers of 0.98 cM. Phylloxera resistance was assessed by monitoring root nodosity number in an in planta experiment and larval development in a root in vitro assay. Nematode resistance was studied using 10-12 month long tests for the selection of durable resistance and rating criteria based on nematode reproduction factor and gall index. A major QTL for phylloxera larval development, explaining more than 70% of the total variance and co-localizing with a QTL for nodosity number, was identified on LG 7 and designated RDV6. Additional QTLs were detected on LG 3 (RDV7) and LG 10 (RDV8), depending on the in planta or in vitro experiments, suggesting that various loci may influence or modulate nodosity formation and larval development. Using a Bulked Segregant Analysis approach and a proportion test, markers clustered in three regions on LG 9, LG 10 and LG 18 were shown to be associated to the nematode resistant phenotype. QTL analysis confirmed the results and QTLs were thus designated respectively XiR2, XiR3 and XiR4, although a LOD-score below the significant threshold value was obtained for the QTL on LG 18. CONCLUSIONS: Based on a high-resolution linkage map and a segregating grapevine backcross progeny, the first QTLs for resistance to D. vitifoliae and to X. index were identified from a muscadine source. All together these results open the way to the development of marker-assisted selection in grapevine rootstock breeding programs based on muscadine derived resistance to phylloxera and to X. index in order to delay GFLV transmission.

Cultivar Diversity of Grape Skin Polyphenol Composition and Changes in Response to Drought Investigated by LC-MS Based Metabolomics.

Phenolic compounds represent a large family of plant secondary metabolites, essential for the quality of grape and wine and playing a major role in plant defense against biotic and abiotic stresses. Phenolic composition is genetically driven and greatly affected by environmental factors, including water stress. A major challenge for breeding of grapevine cultivars adapted to climate change and with high potential for wine-making is to dissect the complex plant metabolic response involved in adaptation mechanisms. A targeted metabolomics approach based on ultra high-performance liquid chromatography coupled to triple quadrupole mass spectrometry (UHPLC-QqQ-MS) analysis in the Multiple Reaction Monitoring (MRM) mode has been developed for high throughput profiling of the phenolic composition of grape skins. This method enables rapid, selective, and sensitive quantification of 96 phenolic compounds (anthocyanins, phenolic acids, stilbenoids, flavonols, dihydroflavonols, flavan-3-ol monomers, and oligomers…), and of the constitutive units of proanthocyanidins (i.e., condensed tannins), giving access to detailed polyphenol composition. It was applied on the skins of mature grape berries from a core-collection of 279 Vitis vinifera cultivars grown with or without watering to assess the genetic variation for polyphenol composition and its modulation by irrigation, in two successive vintages (2014-2015). Distribution of berry weights and δ13C values showed that non irrigated vines were subjected to a marked water stress in 2014 and to a very limited one in 2015. Metabolomics analysis of the polyphenol composition and chemometrics analysis of this data demonstrated an influence of water stress on the biosynthesis of different polyphenol classes and cultivar differences in metabolic response to water deficit. Correlation networks gave insight on the relationships between the different polyphenol metabolites and related biosynthetic pathways. They also established patterns of polyphenol response to drought, with different molecular families affected either positively or negatively in the different cultivars, with potential impact on grape and wine quality.

Quantitative Assessment of Grapevine Wood Colonization by the Dieback Fungus Eutypa lata.

Eutypa lata is a fungal pathogen causing severe dieback in vineyards worldwide. This fungus colonizes vines through pruning wounds, eventually causing a brown sectorial necrosis in wood as well as stunted vegetative growth. Several years may pass between infection and the expression of external symptoms, hindering the rapid evaluation of both grapevine cultivars susceptibility and E. lata variation in aggressiveness. We aimed to develop a rapid quantitative method for the assessment of wood colonization after inoculation of cuttings in controlled conditions. We used several grape cultivars varying in susceptibility in the vineyard and fungal isolates with different levels of aggressiveness to monitor wood colonization during a maximum period of 2 months. Re-isolation allowed demonstration of the effects of both cultivars and fungal isolates on the rate of wood colonization. We also developed a real-time PCR method that was efficient in measuring fungal biomass, which was found to be correlated with isolate aggressiveness based on foliar symptom severity. The real-time PCR approach appears to be a useful technology to evaluate grapevine susceptibility to E. lata, and could be adapted to other pathogens associated with grapevine trunk diseases.

Genetic diversity, linkage disequilibrium and power of a large grapevine (Vitis vinifera L) diversity panel newly designed for association studies.

BACKGROUND: As for many crops, new high-quality grapevine varieties requiring less pesticide and adapted to climate change are needed. In perennial species, breeding is a long process which can be speeded up by gaining knowledge about quantitative trait loci linked to agronomic traits variation. However, due to the long juvenile period of these species, establishing numerous highly recombinant populations for high resolution mapping is both costly and time-consuming. Genome wide association studies in germplasm panels is an alternative method of choice, since it allows identifying the main quantitative trait loci with high resolution by exploiting past recombination events between cultivars. Such studies require adequate panel design to represent most of the available genetic and phenotypic diversity. Assessing linkage disequilibrium extent and panel power is also needed to determine the marker density required for association studies. RESULTS: Starting from the largest grapevine collection worldwide maintained in Vassal (France), we designed a diversity panel of 279 cultivars with limited relatedness, reflecting the low structuration in three genetic pools resulting from different uses (table vs wine) and geographical origin (East vs West), and including the major founders of modern cultivars. With 20 simple sequence repeat markers and five quantitative traits, we showed that our panel adequately captured most of the genetic and phenotypic diversity existing within the entire Vassal collection. To assess linkage disequilibrium extent and panel power, we genotyped single nucleotide polymorphisms: 372 over four genomic regions and 129 distributed over the whole genome. Linkage disequilibrium, measured by correlation corrected for kinship, reached 0.2 for a physical distance between 9 and 458 Kb depending on genetic pool and genomic region, with varying size of linkage disequilibrium blocks. This panel achieved reasonable power to detect associations between traits with high broad-sense heritability (> 0.7) and causal loci with intermediate allelic frequency and strong effect (explaining > 10 % of total variance). CONCLUSIONS: Our association panel constitutes a new, highly valuable resource for genetic association studies in grapevine, and deserves dissemination to diverse field and greenhouse trials to gain more insight into the genetic control of many agronomic traits and their interaction with the environment.

Two-Color Single Hybrid Plasmonic Nanoemitters with Real Time Switchable Dominant Emission Wavelength.

We demonstrate two-color nanoemitters that enable the selection of the dominant emitting wavelength by varying the polarization of excitation light. The nanoemitters were fabricated via surface plasmon-triggered two-photon polymerization. By using two polymerizable solutions with different quantum dots, emitters of different colors can be positioned selectively in different orientations in the close vicinity of the metal nanoparticles. The dominant emission wavelength of the metal/polymer anisotropic hybrid nanoemitter thus can be selected by altering the incident polarization.

Genome-wide prediction methods in highly diverse and heterozygous species: proof-of-concept through simulation in grapevine.

Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.

Haplotype diversity of VvTFL1A gene and association with cluster traits in grapevine (V. vinifera).

BACKGROUND: Interaction between TERMINAL FLOWER 1 (TFL1) and LEAFY (LFY) seem to determine the inflorescence architecture in Arabidopsis. In a parallel way, overexpression of VvTFL1A, a grapevine TFL1 homolog, causes delayed flowering and production of a ramose cluster in the reiterated reproductive meristem (RRM) somatic variant of cultivar Carignan. To analyze the possible contribution of this gene to cluster phenotypic variation in a diversity panel of cultivated grapevine (Vitis vinifera L. subsp. vinifera) its nucleotide diversity was characterized and association analyses among detected sequence polymorphisms and phenology and cluster traits was carried out. RESULTS: A total of 3.6 kb of the VvTFL1A gene, including its promoter, was sequenced in a core collection of 140 individuals designed to maximize phenotypic variation at agronomical relevant traits. Nucleotide variation for VvTFL1A within this collection was higher in the promoter and intron sequences than in the exon regions; where few polymorphisms were located in agreement with a high conservation of coding sequence. Characterization of the VvTFL1A haplotype network identified three major haplogroups, consistent with the geographic origins and the use of the cultivars that could correspond to three major ancestral alleles or evolutionary branches, based on the existence of mutations in linkage disequilibrium. Genetic association studies with cluster traits revealed the presence of major INDEL polymorphisms, explaining 16%, 13% and 25% of flowering time, cluster width and berry weight, respectively, and also structuring the three haplogroups. CONCLUSIONS: At least three major VvTFL1A haplogroups are present in cultivated grapevines, which are defined by the presence of three main polymorphism LD blocks and associated to characteristic phenotypic values for flowering time, cluster width and berry size. Phenotypic differences between haplogroups are consistent with differences observed between Eastern and Western grapevine cultivars and could result from the use of different genetic pools in the domestication process as well as different selection pressures on the development of table and wine cultivars, respectively. Altogether, these results are coherent with previous classifications of grapevine phenotypic diversity mainly based on cluster and berry morphotypes as well as with recent results on the structure of genetic diversity in cultivated grapevine.

Comparative transcriptome of wild type and selected strains of the microalgae Tisochrysis lutea provides insights into the genetic basis, lipid metabolism and the life cycle.

The applied exploitation of microalgae cultures has to date almost exclusively involved the use of wild type strains, deposited over decades in dedicated culture collections. Concomitantly, the concept of improving algae with selection programs for particular specific purposes is slowly emerging. Studying since a decade an economically and ecologically important haptophyte Tisochrysis lutea (Tiso), we took advantage of the availability of wild type (Tiso-Wt) and selected (Tiso-S2M2) strains to conduct a molecular variations study. This endeavour presented substantial challenges: the genome assembly was not yet available, the life cycle unknown and genetic diversity of Tiso-Wt poorly documented. This study brings the first molecular data in order to set up a selection strategy for that microalgae. Following high-throughput Illumina sequencing, transcriptomes of Tiso-Wt and Tiso-S2M2 were de novo assembled and annotated. Genetic diversity between both strains was analyzed and revealed a clear conservation, while a comparison of transcriptomes allowed identification of polymorphisms resulting from the selection program. Of 34,374 transcripts, 291 were differentially expressed and 165 contained positional polymorphisms (SNP, Indel). We focused on lipid over-accumulation of the Tiso-S2M2 strain and 8 candidate genes were identified by combining analysis of positional polymorphism, differential expression levels, selection signature and by study of putative gene function. Moreover, genetic analysis also suggests the existence of a sexual cycle and genetic recombination in Tisochrysis lutea.

ZnO nanowires as effective luminescent sensing materials for nitroaromatic derivatives.

We report on the efficient room-temperature photoluminescence (PL) quenching of ZnO in the presence of 2,4-dinitrotoluene (DNT) vapor and for concentration as low as 180 ppb. Compared to ZnO thin films, ZnO nanowires exhibit a strong (95%) and fast (41 s) quenching of the PL intensity in the presence of DNT vapor. Assuming that the PL quenching is due to a trapping of the ZnO excitons by adsorbed DNT molecules, Monte-Carlo calculations show that the nanometric dimensions as well as the better crystallographic quality (longer mean free path) of the ZnO nanowires result in an enhanced trapping process at the origin of the improved sensing properties of the nanowires. The results demonstrate the importance of nanostructures in improving the sensitivity of ZnO. The study also reveals the sensing capability of ZnO nanowires and paves the path towards the potential realization of low-cost sub-ppb nitroaromatic derivative sensors.

Selection of candidate genes for grape proanthocyanidin pathway by an integrative approach.

Proanthocyanidins (PA) play a major role in plant protection against biotic and abiotic stresses. Moreover these molecules are known to be beneficial for human health and are responsible for astringency of foods and beverages such as wine and thus have a great impact on the final quality of the product. Genes playing a role in the PA pathway are only partially known. The amount of available transcriptomic and genetic data to select candidate genes without a priori knowledge from orthologous function increases every day. However, the methods used so far generate so many candidate genes that it is impossible to validate all of them. In this study, we used an integrative strategy based on different screening methods to select a reduced list of candidate genes. We have crossed results from different screening methods including QTL mapping and three transcriptomic studies to select 20 candidate genes, located in QTL intervals and fulfilling at least two transcriptomic screenings. This list includes three glucosyltransferases, already suspected to have a role in the PA biosynthetic pathway. Among the 17 remaining genes, we selected three genes to perform further analysis by association genetic studies. For each of these genes, we found a polymorphism linked to PA variation. The three genes (VvMybC2-L1, VvGAT-like and VvCob-like), not previously known to play a role in PA synthesis, are promising candidates for further molecular physiology studies.

Genetic structure in cultivated grapevines is linked to geography and human selection.

BACKGROUND: Grapevine (Vitis vinifera subsp. vinifera) is one of the most important and ancient horticultural plants in the world. Domesticated about 8-10,000 years ago in the Eurasian region, grapevine evolved from its wild relative (V. vinifera subsp. sylvestris) into very diverse and heterozygous cultivated forms. In this work we study grapevine genetic structure in a large sample of cultivated varieties, to interpret the wide diversity at morphological and molecular levels and link it to cultivars utilization, putative geographic origin and historical events. RESULTS: We analyzed the genetic structure of cultivated grapevine using a dataset of 2,096 multi-locus genotypes defined by 20 microsatellite markers. We used the Bayesian approach implemented in the STRUCTURE program and a hierarchical clustering procedure based on Ward's method to assign individuals to sub-groups. The analysis revealed three main genetic groups defined by human use and geographic origin: a) wine cultivars from western regions, b) wine cultivars from the Balkans and East Europe, and c) a group mainly composed of table grape cultivars from Eastern Mediterranean, Caucasus, Middle and Far East countries. A second structure level revealed two additional groups, a geographic group from the Iberian Peninsula and Maghreb, and a group comprising table grapes of recent origins from Italy and Central Europe. A large number of admixed genotypes were also identified. Structure clusters regrouped together a large proportion of family-related genotypes. In addition, Ward's method revealed a third level of structure, corresponding either to limited geographic areas, to particular grape use or to family groups created through artificial selection and breeding. CONCLUSIONS: This study provides evidence that the cultivated compartment of Vitis vinifera L. is genetically structured. Genetic relatedness of cultivars has been shaped mostly by human uses, in combination with a geographical effect. The finding of a large portion of admixed genotypes may be the trace of both large human-mediated exchanges between grape-growing regions throughout history and recent breeding.

Transposable elements are a major cause of somatic polymorphism in Vitis vinifera L.

Through multiple vegetative propagation cycles, clones accumulate mutations in somatic cells that are at the origin of clonal phenotypic diversity in grape. Clonal diversity provided clones such as Cabernet-Sauvignon N°470, Chardonnay N° 548 and Pinot noir N° 777 which all produce wines of superior quality. The economic impact of clonal selection is therefore very high: since approx. 95% of the grapevines produced in French nurseries originate from the French clonal selection. In this study we provide the first broad description of polymorphism in different clones of a single grapevine cultivar, Pinot noir, in the context of vegetative propagation. Genome sequencing was performed using 454 GS-FLX methodology without a priori, in order to identify and quantify for the first time molecular polymorphisms responsible for clonal variability in grapevine. New generation sequencing (NGS) was used to compare a large portion of the genome of three Pinot noir clones selected for their phenotypic differences. Reads obtained with NGS and the sequence of Pinot noir ENTAV-INRA® 115 sequenced by Velasco et al., were aligned on the PN40024 reference sequence. We then searched for molecular polymorphism between clones. Three types of polymorphism (SNPs, Indels, mobile elements) were found but insertion polymorphism generated by mobile elements of many families displayed the highest mutational event with respect to clonal variation. Mobile elements inducing insertion polymorphism in the genome of Pinot noir were identified and classified and a list is presented in this study as potential markers for the study of clonal variation. Among these, the dynamic of four mobile elements with a high polymorphism level were analyzed and insertion polymorphism was confirmed in all the Pinot clones registered in France.

Dissecting genetic architecture of grape proanthocyanidin composition through quantitative trait locus mapping.

BACKGROUND: Proanthocyanidins (PAs), or condensed tannins, are flavonoid polymers, widespread throughout the plant kingdom, which provide protection against herbivores while conferring organoleptic and nutritive values to plant-derived foods, such as wine. However, the genetic basis of qualitative and quantitative PA composition variation is still poorly understood. To elucidate the genetic architecture of the complex grape PA composition, we first carried out quantitative trait locus (QTL) analysis on a 191-individual pseudo-F1 progeny. Three categories of PA variables were assessed: total content, percentages of constitutive subunits and composite ratio variables. For nine functional candidate genes, among which eight co-located with QTLs, we performed association analyses using a diversity panel of 141 grapevine cultivars in order to identify causal SNPs. RESULTS: Multiple QTL analysis revealed a total of 103 and 43 QTLs, respectively for seed and skin PA variables. Loci were mainly of additive effect while some loci were primarily of dominant effect. Results also showed a large involvement of pairwise epistatic interactions in shaping PA composition. QTLs for PA variables in skin and seeds differed in number, position, involvement of epistatic interaction and allelic effect, thus revealing different genetic determinisms for grape PA composition in seeds and skin. Association results were consistent with QTL analyses in most cases: four out of nine tested candidate genes (VvLAR1, VvMYBPA2, VvCHI1, VvMYBPA1) showed at least one significant association with PA variables, especially VvLAR1 revealed as of great interest for further functional investigation. Some SNP-phenotype associations were observed only in the diversity panel. CONCLUSIONS: This study presents the first QTL analysis on grape berry PA composition with a comparison between skin and seeds, together with an association study. Our results suggest a complex genetic control for PA traits and different genetic architectures for grape PA composition between berry skin and seeds. This work also uncovers novel genomic regions for further investigation in order to increase our knowledge of the genetic basis of PA composition.

An efficient and rapid protocol for plant nuclear DNA preparation suitable for next generation sequencing methods.

PREMISE OF THE STUDY: In this study, we developed a nuclear DNA extraction protocol for Next Generation Sequencers (NGS). METHODS AND RESULTS: We applied this extraction method to grapevines and coffee trees, which are known to contain many secondary metabolites. The nuclear DNA obtained was sequenced by the 454/GS-FLX method. We obtained excellent results, with less than 4% cytoplasmic DNA, in a similar way to a BAC (Bacterial Artificial Chromosome)-building protocol. We also compared our protocol with a classic DNA extraction using specific cytoplasmic DNA amplification. Results showed a lower cytoplasmic DNA contamination with the new protocol. CONCLUSIONS: The method presented here is fast and economical. The DNA obtained is of high quality, with a low level of cytoplasmic DNA contamination, and very efficient for the construction of sequencing libraries.