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Drosophila suzukii sampling in grapes

Raw data on the percentage of grape berries infested by Drosophila suzukii within Swiss vineyards in respect of site of oviposition in 2017 as well as egg sampling method comparison in 2018 and 2019.

Fig. 4 in Phylogenomics, biogeography, and adaptive radiation of grapes

Fig. 4. Divergence time estimation of Vitis inferred from the MCMC tree program in PAML. Blue bars indicate the 95% highest posterior density credibility interval for node ages. Star indicates calibration point. HPD = Highest Posterior Density; Ma = million years ago.

Fig. 3 in Phylogenomics, biogeography, and adaptive radiation of grapes

Fig. 3. Maximum likelihood (ML) phylogeny and geographic distribution of East Asian grapes. Outgroups are not shown. Approximate ranges of the geographic distribution of the individual species are shown in the maps, using different colors. Tree branches are colored according to the geographic distribution of each species. Orange = Subclade I; yellow = Subclade II; green = Subclade III; Purple and blue tones = Subclade IV. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 1 in Phylogenomics, biogeography, and adaptive radiation of grapes

Fig. 1. Phylogenetic relationship and ancestral areas of subgenus Vitis. (a) Maximum likelihood (ML) phylogeny of Vitis based on 2068 single-copy orthologous genes. All nodes are supported by 100% bootstrap support except from one, whose support is indicated in the figure. Numbers above branches indicate bootstrap support estimated in RAxML while numbers below branches indicate bootstrap support estimated in PhyML. (b) Ancestral area reconstructions of subgenus Vitis using BBM, implemented in RASP. Possible ancestral ranges and their respective probabilities are shown at each node. Most Likely States (MLS) are shown at the center of each node. The four areas of endemism considered are: (A) North America; (B) Europe and West Asia; (C) Northeastern Asia, North China, and the northern edge of the Himalayas; and (D) Central and South China, northern South Asia, and northern Southeast Asia. Dashed arrows indicate inferred migration routes for subgenus Vitis. Three possible migration routes of subgenus Vitis from North America to Euroasia are shown, i.e., the North Atlantic land bridges (NALB), the Bering land bridge (BLB), and intercontinental long distance dispersal (LDD).

Fig. 6 in Phylogenomics, biogeography, and adaptive radiation of grapes

Fig. 6. Ecological environments occupied by various Vitis. (a) V. romanetii is one of the highest climbing species of Vitis, which usually occurs in forest habitats. (b) V. sinocinerea is one of the lowest climbing species of Vitis, which usually occurs in shrubby or open habitats.

Fig. 2 in Phylogenomics, biogeography, and adaptive radiation of grapes

Fig. 2. Maximum likelihood (ML) phylogeny and geographic distribution of North American grapes. Approximate ranges of geographic distribution of species are labeled in the map using different colors. Tree branch colors match the geographic distribution of each species. Blue = Subclade I; Green and purple = Subclade II. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. A.2 in Phylogenomics, biogeography, and adaptive radiation of grapes

Fig. A.2 Gene family analysis. (a) The content of the orthologous genes in different species; (b) Clustering graph of gene family of orthologous genes. (FV: Fragaria vesca; MD: Malus x domestica; VV: Vitis vinifera; PP: Prunus persica; AT: Arabidopsis thaliana).

Figure S2 in Untangling the Evolution of American Wild Grapes: Admixed Species and How to Find Them

Figure S2. (A) One of the two ML-trees inferred by TreeMix under the strictly bifurcating model. The scale bar shows ten times the average standard error (s.e.) of the entries in the sample covariance matrix. Drift parameter is shown on the x-axis. (B) Scaled residuals from the fit of the model to the data. Without migration events 91.7% of the variance in relatedness between taxa was explained by the tree. Colours are described in the palette on the right.

Figure S3 in Untangling the Evolution of American Wild Grapes: Admixed Species and How to Find Them

Figure S3. Scaled residuals from the fit of the model to the data. Allowing eight migration events 98.6% of the variance in relatedness between taxa was explained by the tree. Colours are described in the palette on the right.

FIGURE 3 in Untangling the Evolution of American Wild Grapes: Admixed Species and How to Find Them

FIGURE 3 | (A) Maximum Likelihood (ML)-tree inferred by TreeMix allowing eight migration events. Letters A–H refer to migration edges as defined in Table 1. Migration H, not confirmed by the f4 statistic after the Holm-Bonferroni correction (see Table 3), is shown using a two-dashed line. Migration arrows are colored according to their weight and colors are explained in the palette on the left. The scale bar shows ten times the average standard error (s.e.) of the entries in the sample covariance matrix. Drift parameter is shown on the x-axis.

FIGURE 2 in Untangling the Evolution of American Wild Grapes: Admixed Species and How to Find Them

FIGURE 2 | (A) The Maximum Likelihood (ML)-tree inferred by TreeMix under the strictly bifurcating model. The scale bar shows ten times the average standard error (s.e.) of the entries in the sample covariance matrix. Drift parameter is shown on the x-axis. (B) Scaled residuals from the fit of the model to the data. Without migration events 91.7% of the variance in relatedness between taxa was explained by the tree. Colors are described in the palette on the right.

Figure S1 in Untangling the Evolution of American Wild Grapes: Admixed Species and How to Find Them

Figure S1: The decay of linkage disequilibrium (LD) in: V. acerifolia, V. aestivalis, V. aestivalis var. aestivalis, V. champinii, V. cinerea, V. cinerea var. helleri, V. labrusca, V. riparia, V. rupestris, V. vinifera subsp. vinifera, V. vulpina. LD was estimated calculating the pairwise squared correlation based on genotypic allele counts (--r2 option in PLINK; Purcell et al. 2007) for all intrachromosomal SNP loci up to 500 kb. Each point represents the median r2 value and the mean physical distance from bins of 75 pairwise SNP comparisons. LD decay is rapid in all species considered. N: the number of individuals sampled to estimate LD; Bin width: the number of pairwise r2 values included in each bin; dotted black lines indicate r2= 0.2. Physical inter-marker distance is expressed as kilobase pairs (kb).

FIGURE 1 in Untangling the Evolution of American Wild Grapes: Admixed Species and How to Find Them

FIGURE 1 | (A) Linkage disequilibrium (LD) decay in ten grape species. The median r2 calculated in bins of 75 pairwise SNP comparisons was plotted against the mean physical distance of each bin (kb). Sample size for each species is shown in figure. Dotted line indicates r2 = 0.2. (B) Multistep procedure followed to identify the appropriate SNP block size used in TreeMix analysis. The SNP block size tested at each step is shown above plots. The physical distance (kb) between midpoints of consecutive blocks placed on the same chromosome is shown on y-axis while the x-axis shows the number of pairwise distances computed at each step. The dashed red line represents the assumed distance threshold (i.e., 200 kb).

FIGURE 4 in Untangling the Evolution of American Wild Grapes: Admixed Species and How to Find Them

FIGURE 4 | The figure shows the phylogenetic relationships of grapes referred to this work. Linking lines between corresponding tips are used to highlight changes in tree topology and taxa placements due to the addition of migration events. Left: the strict consensus tree between the two the best-scoring Maximum Likelihood (ML) tree topology obtained from 400 ML searches performed by TreeMix under the strictly bifurcating model. Right: strict consensus tree of the forty ML trees inferred by TreeMix allowing nine migration events. Bootstrap values (500 replicates) are shown for each node.

Fig. 2 A in Multigenic resistance to Xylella fastidiosa in wild grapes (Vitis sps.) and its implications within a changing climate

Fig. 2 A Manhattan plot of the V. arizonica genome showing markers associated with bacterial load. The plot denotes each of the 19 chromosomes for haplotype 1. Each circle represents a SNP with a corresponding p value, based on EMMAX genome-wide association analysis. The 25 SNPs that were detected in two separate GWA analyses are circled in red and define the 8 peaks of association, which are numbered as P1, P2, etc., and referred to in the text. In addition to SNPs, the locations of significantly associated kmers and CNVs are provided when they overlap with a SNP-defined peak. The colored horizontal lines represent the cut-off p-values (P <0.05, Bonferroni corrected) for the different marker types. Significant (P <0.05, Bonferroni corrected) kmers and CNVs are represented by red and blue triangles, respectively.

Fig. 1 Vitis arizonica sampling and phenotypes. A in Multigenic resistance to Xylella fastidiosa in wild grapes (Vitis sps.) and its implications within a changing climate

Fig. 1 Vitis arizonica sampling and phenotypes. A map of the Southwestern United States and Northern Mexico indicates sampling locations of the n = 167 V. arizonica accessions used in this study. The color of sample locations (circles) are colored according to their resistance phenotype, as measured by bacterial load (CFU/mL). The histogram of phenotypes (in CFU/mL) is to the right of the map. Map generation relied on information from GADM, a publicly available database (http:gadm.org).

Fig. 5 in Multigenic resistance to Xylella fastidiosa in wild grapes (Vitis sps.) and its implications within a changing climate

Fig. 5 Relationships among resistance, genetic markers and bioclimatic data. a The estimated relative importance, from GF modeling, of each of the bioclimatic variables tested. The y-axis is a measure of the importance of various variables to explain the model - i.e., the relative importance of each bioclimatic variable for predicting changes in allele frequency across the landscape. Each boxplot denotes the average inferred importance of the bioclimatic variable, with the whiskers plotting the standard deviation of 1000 separate analyses (gray dots). BIO8 was estimated to have the biggest impact on the model in all 1000 analyses. b The turnover function showing the temperature range of BIO8 on the x-axis and the change in the genetic composition on the y-axis. The circles represent individuals that are colored by resistance (gray) or susceptible (white). c Individual predictors in a linear model to predict resistance levels (CFU/ml). The label score_ref represents sets of 1000 randomly chosen sets of 25 SNPs; K1 and K2 are the proportion of the assignments to each admixture group for each individual. The other predictors include bioclimatic variables and genomic data, as listed in the text, each evaluated 1000 times with bootstrapped datasets. Each boxplot reports the second and third quartiles, with median values in the square and circles showing outliers. The barplot whiskers report standard deviation, and the dashed horizontal line reflects the median value of 1000 replicates of the Rpd score. d The density distribution of BIO8 for a global database of locations of Xylella fastidiosa detection.

Fig. 4 in Multigenic resistance to Xylella fastidiosa in wild grapes (Vitis sps.) and its implications within a changing climate

Fig. 4 The presence of resistance and susceptibility kmers in different data sets. a Analyses within the V. arizonica sample set. The top-left graph indicates the 99 different resistance (R-kmers) kmers across the x-axis, with their detection frequency across the resistant (CFU/mL <13) accessions. The top-right graph plots the average detection frequency of susceptibility kmers (S-kmers). The bottom-left and bottom-right graph are similar, they but show R-kmer and S-kmer detection frequencies among susceptible accessions. b The same graphs as in A, but the top graphs plot R-kmer and S-kmer detection frequencies for the five V. vinifera cultivars bred for PD resistance by backcrossing to V arizonica, while the bottom graphs represent susceptible V. vinifera cutlivars. c. Plots of kmer frequencies in six Vitis species. The species phylogeny is shown on the left, with the average detection frequency of R-kmers shown in red dot. The gray dots represent average detection frequencies of randomly chosen kmers that had similar population frequencies in V. arizonica as the set of R kmers. Whiskers denote 95% confidence intervals.