SNiPlay: a web-based tool for detection, management and analysis of SNP (C900)

The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine genetic data with the genome's structure and with external data available. In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates: 1) a pipeline, freely accessible through the internet, combining existing software with new tools to detect SNPs and to compute different kinds of statistical indices and graphical layouts for SNP data. From Sanger sequencing traces, multiple sequence alignments or genotyping data given as input, SNiPlay detects SNPs and insertion/deletion events. In a second time, it sends sequences and genotyping data into a series of modules in charge of various post-processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and networking, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D). 2) a database storing polymorphisms, genotyping data and sequences of grapevine produced by nationally-funded public projects. It allows one to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats. SNiPlay is available at: http://www.sniplay.cirad.fr/. (Texte intégral

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

UMR-AGAP Equipe DAVV (Diversité, adaptation et amélioration de la vigne) ; équipe ID (Intégration de Données)International audienceAbstractBackgroundAs 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.ResultsStarting 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).ConclusionsOur 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

Identification of stable QTLs for vegetative and reproductive traits in the microvine (Vitis vinifera L.) using the 18 K Infinium chip

UMR AGAP - équipe DAAV - Diversité, adaptation et amélioration de la vigne[b]Background[/b] [br/]The increasing temperature associated with climate change impacts grapevine phenology and development with critical effects on grape yield and composition. Plant breeding has the potential to deliver new cultivars with stable yield and quality under warmer climate conditions, but this requires the identification of stable genetic determinants. This study tested the potentialities of the microvine to boost genetics in grapevine. A mapping population of 129 microvines derived from Picovine x Ugni Blanc flb, was genotyped with the Illumina® 18 K SNP (Single Nucleotide Polymorphism) chip. Forty-three vegetative and reproductive traits were phenotyped outdoors over four cropping cycles, and a subset of 22 traits over two cropping cycles in growth rooms with two contrasted temperatures, in order to map stable QTLs (Quantitative Trait Loci). [br/][b]Results[/b] [br/]Ten stable QTLs for berry development and quality or leaf area were identified on the parental maps. A new major QTL explaining up to 44 % of total variance of berry weight was identified on chromosome 7 in Ugni Blanc flb, and co-localized with QTLs for seed number (up to 76 % total variance), major berry acids at green lag phase (up to 35 %), and other yield components (up to 25 %). In addition, a minor QTL for leaf area was found on chromosome 4 of the same parent. In contrast, only minor QTLs for berry acidity and leaf area could be found as moderately stable in Picovine. None of the transporters recently identified as mutated in low acidity apples or Cucurbits were included in the several hundreds of candidate genes underlying the above berry QTLs, which could be reduced to a few dozen candidate genes when a priori pertinent biological functions and organ specific expression were considered. [br/][b]Conclusions[/b] [br/]This study combining the use of microvine and a high throughput genotyping technology was innovative for grapevine genetics. It allowed the identification of 10 stable QTLs, including the first berry acidity QTLs reported so far in a Vitis vinifera intra-specific cross. Robustness of a set of QTLs was assessed with respect to temperature variatio

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

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>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 (<it>VvLAR1</it>, <it>VvMYBPA2</it>, <it>VvCHI1</it>, <it>VvMYBPA1</it>) showed at least one significant association with PA variables, especially <it>VvLAR1 </it>revealed as of great interest for further functional investigation. Some SNP-phenotype associations were observed only in the diversity panel.</p> <p>Conclusions</p> <p>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.</p

Promoting Grass in Horse Diets and Implementing Sustainable Deworming: ‘Équipâture’ Programme

The Équipâture programme examined the grazing regimes and parasite statuses of horses on 12 study farms. Its research yielded useful results. Rotational grazing of mares, foals, and school riding horses allowed animals to meet their nutritional needs without any supplements (50 ares/LU in the spring; 80 ares/LU in the summer). During the winter, haylage met the high demands of mares and foals. Late-cut hay could not, and there was a risk of P, Cu, and Zn deficiencies when horses were given a 100% hay diet. A sustainable approach to deworming was implemented on the farms. Based on faecal analysis, animals were assigned a parasite excretion status. As a result of this categorisation, only half of the animals were dewormed. This method helped limit deworming costs and the development of parasite resistance to dewormers

NIRS as a high-throughput phenotyping tool for assessing the diversity of leaf functioning under water deficit in a large grapevine panel

Water resource is a major limiting factor impacted by climate change, threatening the yield and quality of grapevine production. Understanding the ecophysiological mechanisms involved in response to water deficit is crucial to select new varieties more drought-tolerant. A major bottleneck that hampers such advances is the lack of methods for measuring functioning traits on thousands of leaves as required for genetic analyses. Recent studies have highlighted the interest of near-infrared spectroscopy (NIRS) and chlorophyll fluorescence for high-throughput evaluation of leaf functioning traits. The aim of this study is to develop these methods, and test their robustness to facilitate their deployment for phenotyping the genetic diversity of grapevine. 246 genotypes, representative of the genetic diversity of the species Vitis vinifera, were phenotyped over two consecutive years. In 2021, the genotypes were grown in pots outdoors under non-limiting irrigation conditions, while in 2022, the same potted genotypes were subjected to three different water scenarios (i. Well-watered, ii. Moderate water deficit, iii. Severe water deficit) in a greenhouse (PhenoArch high-throughput phenotyping platform). To evaluate traits related to carbon and water functioning across the entire panel, a subset of genotypes were phenotyped by combining i/ low-throughput devices to precisely measure ecophysiological traits, and ii/ innovative high-throughput portable devices to measure NIRS, porometry and chlorophyll fluorescence. These data enabled the creation of partial least squares regression (PLSR) models using both low- and high-throughput data to predict ecophysiological traits. Leaf mass per area and leaf water content were well predicted by spectrometers (R² > 0.7). Photosynthesis, on the other hand, was well predicted by chlorophyll fluorescence and porometry data. The robustness of the predictive models was tested between experiments by comparing models calibrated with data from one experiment to predict data from the second one. The robustness of the models was dependent on the trait and the high-throughput device used. The prediction of leaf mass per area, using NIRS, appeared to be accurate and stable between experiments. Intra-experiment robustness analysis showed that water deficit can impact the quality of trait predictions, particularly those related to water, such as water content and water use efficiency. The R² and RMSE parameters provided additional information, especially as water deficit affected trait variability. The prediction of these traits was less accurate when applied on a plant that had been grown under severe water deficit. Compelling models will be employed to predict these traits across the entire panel, enabling their use in genetic analysis

SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects

<p>Abstract</p> <p>Background</p> <p>High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.</p> <p>Results</p> <p>In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:</p> <p>1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).</p> <p>Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.</p> <p>2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats.</p> <p>Conclusions</p> <p>Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.</p> <p>SNiPlay is available at: <url>http://sniplay.cirad.fr/</url>.</p

Evolution de la diversité génétique intra-population et de sa structure : étude d'un modèle de simulation spatialisé en vue de la gestion des ressources génétiques forestières tropicales

Ce travail est une contribution à l'acquisition des bases théoriques nécessaires à l'élaboration de plans d'aménagement des forêts tropicales prenant en compte la gestion dynamique in situ des ressources génétiques forestières. Deux volets complémentaires sont abordés : d'une part, l'élaboration et l'étude d'un modèle spatialisé d'évolution de la diversité génétique à l'intérieur d'une population finie; d'autre part, la caractérisation du régime de reproduction et la description de la diversité génétique dans une population de Carapa procera (Meliaceae); une espèce d'arbre de la forêt guyanaise. Le modèle utilisé est un modèle stochastique d'isolement par la distance pour une population finie spacialement structurée, avec possibilité d'autofécondation, de chevauchement des générations, de sélection en faveur des hétérozygotes, et d'exploitation d'une partie des individus à intervalles de temps réguliers. Des simulations basées sur les hypothèses de ce modèle ont été utilisées pour l'étude des variations simultanées des différentes variables d'entrée : densité, taille de la population, distances de pollinisation, distances de dissémination, chevauchement des générations coefficient de sélection et taux d'exploitatio