Open Access Highly Accessed Research article

Genetic diversity and population structure assessed by SSR and SNP markers in a large germplasm collection of grape

Francesco Emanuelli1, Silvia Lorenzi1, Lukasz Grzeskowiak1, Valentina Catalano1, Marco Stefanini1, Michela Troggio1, Sean Myles2, José M Martinez-Zapater3, Eva Zyprian4, Flavia M Moreira15 and M Stella Grando1*

Author Affiliations

1 Department of Genomics and Biology of Fruit Crops, IASMA Research and Innovation Centre, Fondazione Edmund Mach - Via E. Mach 1, San Michele all'Adige, TN, 38010, Italy

2 Department of Plant and Animal Sciences, Faculty of Agriculture, Dalhousie University, Truro, Nova Scotia, B2N 5E3, Canada

3 Instituto de Ciencias de la Vid y del Vino (CSIC, UR, Gobierno de La Rioja), C/ Madre de dios 51, Logroño, 26006, Spain

4 JKI Institute for Grapevine Breeding Geilweilerhof, Siebeldingen, 76833, Germany

5 Instituto Federal de Santa Catarina, Rua José Lino Kretzer 608 - Praia Comprida, São José, Santa Catarina, 88130-310, Brasil

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BMC Plant Biology 2013, 13:39  doi:10.1186/1471-2229-13-39

Published: 7 March 2013

Additional files

Additional file 1: Table S1:

Groups of accessions with the identical SSR profile that included true-to-type Italian varieties. Names of accessions registered as synonymous to the true-to-type prime name are indicated in bold (Vitis International Variety Catalogue http://www.vivc.de webcite). Table S2. Minimum and maximum dates of the beginning of phenological stages for the “phenological core collection” in the three growing seasons (2008-2010). The E-L numbers indicate major vine growth stages according to the modified Eichhorn-Lorenz system [60]. Table S3. SSR markers and multiplex PCR conditions, allele size range and marker profiles of the grapevine cultivars (Pinot noir and Sangiovese) used as internal control for genotyping. a SSR markers with the same number were amplified in a single PCR mix (all primers pooled in the PCR mix). * Reference set of SSR markers used for cultivar identification. Table S4. A total of 384 SNPs selected for genotyping of the FEM grape germplasm collection. Chr - chromosome carrying the SNP according to the reference grapevine genome (Pinot Noir, 8x); LG – linkage group; MAF – minor allele frequency. Source of markers: No. 1-122: [62]; No. 123-286: [19]; No. 287-374: [63]; 375-383: Zyprian et al. (in preparation); 384: [39]. Table S5. Summary statistics of genetic variation at each of the 22 SSR loci in the FEM grape germplasm collection. Total – pooled sample treated as a single population; N – sample size; n – mean sample size over loci; A – number of different alleles; a – mean number of alleles per locus; AE – effective number of alleles; Apr – number of alleles unique to a single population; HO – observed heterozygosity; HE – unbiased expected heterozygosity; F – fixation index (inbreeding coefficient). Table S6. Percent population assignment based on SSR and SNP marker datasets. Each value gives the percentage of individuals that had ≥0.8 membership in a subpopulation using the STRUCTURE analysis (K=2 to 6, with SSR or SNP dataset). Table S7. Groups of V. vinifera ssp. sativa inferred by hierarchical STRUCTURE using SSR and SNP datasets. Listed are the accessions common in the four clusters distinguished using SSR and SNP datasets (i.e. in VV1 and VV1I, VV2 and VV2I, VV3 and VV3I, VV4 and VV4I). The true-to-type samples from these four groups are indicated in bold. Table S8. Common cluster pairwise FST estimates (P=0.00, 1000 permutations).

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Additional file 2:

Redundancy curves developed for genetic core collections G-58 and G-110 using the M-method (in blue) and random sampling (in red) with standard deviations, captured in ten independent sampling runs. Plot shows the accumulation of allelic diversity with increasing core size. The core G-110 obtained using the M-method was built considering samples from the core G-58 as fixed.

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Additional file 3:

Estimated number of clusters obtained with STRUCTURE for K values from 1 to 20 using SSR data. Graphical representation of (a) estimated mean L(K) and (b) its derivative statistics ΔK. (c) Table summarizing parameters of different STRUCTURE simulations performed for each preset K: mean likelihoods of models, mean similarity coefficients, clusteredness, and their standard deviations, ΔK and significance of Wilcoxon test.

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Additional file 4:

Estimated number of clusters obtained with STRUCTURE for K values from 1 to 20 using SNP data. Graphical representation of (a) estimated mean L(K) and (b) its derivative statistics ΔK. (c) Table summarizing parameters of different STRUCTURE simulations performed for each preset K: mean likelihoods of models, mean similarity coefficients, clusteredness, and their standard deviations, ΔK and significance of Wilcoxon test.

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Additional file 5:

Neighbour-joining tree and inferred population structure of the grape germplasm collection, calculated from the dataset of 22 SSR markers and 353 SNPs across 1146 individuals using structure analysis (K=5). Each individual is represented by a line partitioned in five coloured segments (the individual’s estimated membership fractions to each one of the five clusters). Threshold of the membership coefficient Q was 0.80 for the SSR dataset and 0.65 for the SNP dataset.

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Additional file 6:

Physical position of SNP and SSR markers. The map shows the position (in megabases) of SNPs (in black) and SSRs (in red) for each chromosome within the 8X reference genome. Markers with unknown or uncertain physical position are not shown.

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