Genetic Structuring and Parentage Analysis for Evolutionary Studies in Grapevine: Kin Group and Origin of the Cultivar Sangiovese Revealed

Genetic structuring and parentage analysis were performed on a very large database comprising 2786 unique multilocus genotypes [20 nuclear simple sequence repeats (nSSRs)] of Vitis vinifera L. ssp. sativa (DC.) Hegi with a special focus on Tuscan cultivars to reveal the parentage and history of the cultivar Sangiovese, the most important cultivar of Italy. For this cultivar, the authors also analyzed clones and synonyms, investigating its genetic origin and intracultivar diversity. Known synonyms of 'Sangiovese' were confirmed and new ones were revealed with cultivars outside Tuscany. Some synonyms were invalidated, and unexpected homonyms were identified. The absence of true intracultivar variability leads to the rejection of a polyclonal origin for 'Sangiovese'. The existence of an Italian genetic pool composed of ancient cultivars including Sangiovese was demonstrated by analyzing the entire set of 2786 cultivars. Ten individuals compose the kin group of 'Sangiovese', including two offspring: 'Ciliegiolo' and 'Catarratto bianco faux'. Despite the large presence and long history of 'Sangiovese' in the Tyrrenian area, its kin group is unexpectedly composed of a majority of ancient cultivars that are largely diffused in far southern Italy, which leads to the hypothesis of a Sicilian origin for 'Sangiovese'. Analysis of the Tuscan pool revealed large kin groups for cultivars Mammolo and Garganega, demonstrating their contribution to the genetic diversification in the Tyrrenian area. This work contributes to the understanding of grapevine diversification, evolution, and history in Italy and Europe

A Gene-Phenotype Network Based on Genetic Variability for Drought Responses Reveals Key Physiological Processes in Controlled and Natural Environments

Identifying the connections between molecular and physiological processes underlying the diversity of drought stress responses in plants is key for basic and applied science. Drought stress response involves a large number of molecular pathways and subsequent physiological processes. Therefore, it constitutes an archetypical systems biology model. We first inferred a gene-phenotype network exploiting differences in drought responses of eight sunflower (Helianthus annuus) genotypes to two drought stress scenarios. Large transcriptomic data were obtained with the sunflower Affymetrix microarray, comprising 32423 probesets, and were associated to nine morpho-physiological traits (integrated transpired water, leaf transpiration rate, osmotic potential, relative water content, leaf mass per area, carbon isotope discrimination, plant height, number of leaves and collar diameter) using sPLS regression. Overall, we could associate the expression patterns of 1263 probesets to six phenotypic traits and identify if correlations were due to treatment, genotype and/or their interaction. We also identified genes whose expression is affected at moderate and/or intense drought stress together with genes whose expression variation could explain phenotypic and drought tolerance variability among our genetic material. We then used the network model to study phenotypic changes in less tractable agronomical conditions, i.e. sunflower hybrids subjected to different watering regimes in field trials. Mapping this new dataset in the gene-phenotype network allowed us to identify genes whose expression was robustly affected by water deprivation in both controlled and field conditions. The enrichment in genes correlated to relative water content and osmotic potential provides evidence of the importance of these traits in agronomical conditions

Results of the sparse Partial Least Squares (SPLS) analysis on plants under FDS (A) and FIS (B).

<p>Plots show respectively the repartition of the morphophysiological variables (left) and individuals (right) along the first two components of the SPLS. Morphophysiological variables are carbon isotope discrimination (CID), collar diameter (CoD), Transpiration rate (E), Integrated Transpired Water (ITW), Leaf Mass per Area (LMA), Osmotic Potential (OP), Plant Height (PHe), Relative Water Content (RWC) and Total plant Leaf Area (TLA). Triangles correspond to treated plants whereas circles correspond to their untreated counterparts. Genotypes are color-coded as follows: Inedi (black), Tekny (gray), Melody (red), SF109 (turquoise), SF326 (yellow), SF193 (magenta), SF028 (green) and SF107 (blue).</p

Gene-Phenotype sub-network produced by SPLS, based on responses of eight sunflower genotypes to two drought stress scenarios implemented in controlled environment.

<p>Only genes regulated by drought stress in field conditions are shown. Each ellipse represents one gene. Blue, red and purple edges indicate, respectively, whether the gene-phenotype association exists under FDS, FIS or both stress scenarios. Sunflower Heliagene cluster IDs are shown when meaningful names of Arabidopsis homologs are not available. Gray squares represent phenotypic responses; OP: Osmotic Potential, E: Transpiration Rate, RWC: Relative Water Content, ITW: Integrated Transpired Water, PHe: Plant Height.</p

GO term enrichment test results for genes showing ANOVA effects for two drought scenarios.

<p>GO term enrichment tests performed on groups of genes showing genotype, treatment and/or genotype*treatment interaction (g*t) effects in ANOVAs carried out with eight sunflower genotypes undergoing two drought stress scenarios in controlled environment: Fixed Duration Stress (FDS) and Fixed Intensity Stress (FIS). Reference dataset corresponded to the GO terms available for the 32 423 sunflower clusters used for this work. Tests were performed on the AgriGO website <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0045249#pone.0045249-Du1" target="_blank">[105]</a>.</p

Dendograms and heatmaps of genes and individuals both under FDS (A) and FIS (B).

<p>Triangles correspond to treated plants whereas circles correspond to their untreated counterparts. Genotypes are color-coded as follows: Inedi (black), Tekny (gray), Melody (red), SF109 (turquoise), SF326 (yellow), SF193 (magenta), SF028 (green) and SF107 (blue).</p

Gene-Phenotype network produced by SPLS, based on responses of eight sunflower genotypes to two drought stress scenarios implemented in controlled environment.

<p>Genes presenting absolute correlation scores higher than 0.65 with at least one morpho-physiological variable are represented. Each circle represents one gene. Blue, red and purple edges indicate, respectively, whether the gene-phenotype association exists under FDS, FIS or both stress scenarios. Each gene circle is split in three slices displaying ANOVA results. Yellow, red and black slices represent, respectively, treatment effect under FDS (moderate stress responsive genes), treatment effect under FIS (severe stress responsive genes), and g*t effect under FIS (gene likely to explain genotypic differences in stress responses). Numbers of genes for each combination of ANOVA effects are shown for each gene-phenotype group. Phenotypic responses are in gray squares, OP: Osmotic Potential, LMA: Leaf Mass Area, E: Transpiration Rate, RWC: Relative Water Content, ITW: Integrated Transpired Water, PHe: Plant Height.</p

Evolution of Fraction of Transpirable Soil Water (FTSW) during water deprivation.

<p>Each line reflects the average values of three values for each genotype either under FDS or under FIS. Vertical dotted line indicates the date of the FDS tissue collection. Horizontal dotted line indicates the FTSW level at which FIS collection was carried out. Triangles correspond to treated plants whereas circles correspond to their untreated counterparts. Genotypes are color-coded as follows: Inedi (black), Tekny (gray), Melody (red), SF109 (turquoise), SF326 (yellow), SF193 (magenta), SF028 (green) and SF107 (blue).</p