Mol Biotechnol DOI 10.1007/s12033-013-9729-6

RESEARCH

Morphological Variability in Leaves and Molecular Characterization of Novel Table Grape Candidate Cultivars (Vitis vinifera L.) Vittorio Alba • Carlo Bergamini • Maria Francesca Cardone Marica Gasparro • Rocco Perniola • Rosalinda Genghi • Donato Antonacci

•

Ó Springer Science+Business Media New York 2014

Abstract The present work report the characterization of twenty-one table grapes candidate cultivars plus five registered ones included as reference, by means of 47 ampelographic traits, 23 ampelometric measurements and six microsatellite loci. The final goal of the research was to analyse the possibility of reducing the number of morphological and molecular tools required for a precise and effective description of a grape genotype or cultivar. This would be of great help for future biodiversity description on a larger sample of more than 300 table grapes accessions today grown at the ‘Consiglio per la Ricerca e la sperimentazione in Agricoltura (C.R.A.)—Unita` di ricerca per l’uva da tavola e la vitivinicoltura in ambiente mediterraneo (Bari—Italy)’. OIV ampelographic traits showed a clear distinction among all twenty-six genotypes analysed,

V. Alba  C. Bergamini  M. F. Cardone  M. Gasparro  R. Perniola  R. Genghi  D. Antonacci (&) Consiglio per la Ricerca e la sperimentazione in Agricoltura CRA, Unita` di ricerca per l’uva da tavola e la vitivinicoltura in ambiente mediterraneo, Via Casamassima 148, 70010 Turi, BA, Italy e-mail: [email protected] V. Alba e-mail: [email protected] C. Bergamini e-mail: [email protected] M. F. Cardone e-mail: [email protected] M. Gasparro e-mail: [email protected] R. Perniola e-mail: [email protected] R. Genghi e-mail: [email protected]

suggesting the relevant morphological variability investigated. Principal component analysis based on ampelometric traits revealed main veins ON3, ON4 and O3N4; ratios between main veins; angles between main veins and of petiolar sinus, to be the most effective records in differentiating cultivars, for a total variation of 69.9 % described by the first three components. Molecular analysis based on six microsatellite loci was performed on all genotypes, providing a detailed molecular profile and a dendrogram of genetic similarity, in which all genotypes were clearly distinguishable. Finally, with the goal of using the minimum possible number of markers to differentiate genotypes, microsatellites VVMD5 and VVMD27 were selected to be sufficient to distinguish among all the candidate cultivars included in the analysis, representing a possible ‘step by step’ approach when a molecular characterization has to be undertaken on a large number of genotypes, by first testing few markers and increasing their number only if necessary. Keywords Table grape  Ampelography  Ampelometry  Microsatellites

Introduction Plant breeding in Vitis vinifera L. aims to combine agronomic and productive desirable traits mostly by intraspecific and interspecific crosses. The selection of progenies carrying genetic combinations that better meet pedoclimatic conditions in different geographic areas is a wellestablished strategy for varietal constitution in table grapes. This is possible thanks to the exploitation of the high level of natural biodiversity principally present in the Asian Middle-East and in the Mediterranean basin—centres of

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origin and domestication of Vitis vinifera L, respectively [1]. Anyway, the arrival of diseases (powdery mildew and downy mildew) and pests (phylloxera) from America in the late nineteenth and early twentieth century that caused the loss of grape diversity especially in Europe [2] contemporary represented a stimulus for a modern breeding approach. This has led to the achievement of many Vitis vinifera L. crosses which yielded numerous new table grape cultivars and several crosses today still under evaluation and characterization [3]. The total number of grapevine cultivars in ampelographic collections worldwide is estimated to be up to 15,000 and the number of cultivars in use is very large. Even if the plants are in excellent condition, it is extremely difficult to differentiate all varieties by morphological features [4], since a large number of individuals with considerable number of repetition in several vegetation seasons is needed. Only in that way it would be possible to keep environmental variability low and identify the most informative phenotypic characters. To this, molecular analyses supporting ampelographic and ampelometric approaches represent fundamental tools in table grapes biodiversity studies, in breeding programmes, and in cultivar identification and characterization. In particular, ampelography is the first step in grapevine selection, in solving different classification problems and in the description of accessions to detect close agronomic mutations [5–7] and usually is sufficient to differentiate grapevine varieties [8]. Due to the number of OIV codes to be recorded for an exhaustive description of a grape cultivar, a list of fourteen primary descriptors was defined, but in cases when only the mature leaf is available for description, these are not able to describe in depth the biodiversity investigated. Since ampelography is based on subjective visual notes and often led in the past to erroneous or not comparable results, the ‘Organisation Internationale de la Vigne et du Vin’—OIV set a descriptor list for grapevine in order to standardize the description of morphological traits [9], by also including metric measurements like ampelometric calculations on mature leaf. The list comprises 30 OIV codes for mature leaf and 17 codes extrapolated from ampelometric measurements and converted in ampelographic discrete classes (codes 601–618). Systems to digitalize pictures of mature leaves and to calculate ampelometric traits are today available and user friendly and allow researchers to save time and to operate indoor. Metric scale measurements are more objective than discrete classes that tend to reduce the variability of biodiversity analysed, and consequently can be efficiently considered without being converted in ampelographic classes. The length of each main vein and their ratios, leaf size, leaf length to width ratio and the angles between main veins represent a complementary tool for an objective description of grapevine cultivars. Indeed,

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ampelometry alone is not sufficient to identify a cultivar and, therefore, needs to be implemented with other characteristics [10]. Molecular markers and in particular microsatellites are fundamental for cultivar characterization in table grapes, to solve cases of homonyms and synonyms, in establishing the relationship within and among grape cultivars and can be efficiently employed in mapping strategies that involve important genetic traits or in the development of a core collection that relies on the discovery of morphological and molecular polymorphisms in a small set of genotypes that are as representative as possible of available genetic diversity. Such a concept was first proposed by Frankel and Brown [11] under the name of core collection. Various programmes have been initiated on different plant materials to safeguard, collect and establish collections, complemented by diversity evaluations [12]. Le Cunff et al. [13], when creating a core collection of Vitis vinifera L., reported how a sample of 24 cultivars from a germplasm collection of more than 2,000 genotypes covered 73 and 88 % of total SSR and SNP variation investigated, respectively. The aim of the present work was to describe and characterize morphological and molecular variability of twenty-one novel table grape candidate cultivars (Vitis vinifera L.) plus five registered ones included as reference, by means of 47 ampelographic, 23 ampelometric traits on mature leaf and six microsatellite loci. The possibility of reducing the number of descriptors for a leaner characterization by focusing on the most suitable and effective OIV codes, comprising microsatellites, in differentiating table grapes genotypes was investigated, in order to establish the basis for future studies of the large biodiversity enclosed in the ex-situ field collection held at the ‘Consiglio per la Ricerca e la sperimentazione in Agricoltura—CRA—Unita` di ricerca per l’uva da tavola e la vitivinicoltura in ambiente mediterraneo’ consisting of more than 300 accessions and cultivars. This could be of help to identify a minimum number of characters adequate to study and distinguish larger variability such as breeding materials.

Materials and Methods Plant Material The study was conducted on a total of 26 table grape genotypes (Table 1). Twenty-one of them were novel candidate cultivars still under characterization, while five cultivars, regularly registered in the Italian registry grape varieties, were included in the research as reference: Cardinal N., Conegliano 218 N., Delizia di Vaprio B., Italia B.

Mol Biotechnol

and Sugraone B. All genotypes were grafted onto 1103 Paulsen (V. berlandieri x V. rupestris), spaced 2.5 m between rows 9 1 m on the row, in an ex-situ collection of the experimental field of the ‘CRA—Unita` di ricerca per l’uva da tavola e la vitivinicoltura in ambiente mediterraneo’; 20 full-developed leaves were harvested in 2012 and 2013 from the middle third of several shoots as required by OIV descriptors on one pair of vines for each genotype. Ampelography Forty-seven ampelographic characters were measured on each collected mature leaf on the base of a list of descriptors developed by the Organisation Internationale de la Vigne et du Vin [9], (Tables 2, 3). Ampelographic readings were conducted by two different operators in order to reduce the subjectivity of relieves and compared with ampelographic description reported in the Database of

Table 1 List of twenty-one novel table grape candidate cultivars and five cultivars with relative pedigree available in bibliography for a total of twenty-six genotypes Genotype

Pedigree as given in bibliography

89IxU119

Italia

the Italian Agriculture Ministry (http://catalogoviti.poli ticheagricole.it/home.php). Ampelometry A digital photo of all 20 leaves for each genotype/year was taken and processed by Superampelos 2.0 [15] to obtain averages of 23 ampelometric parameters including leaf area (Fig. 1; Tables 4, 5). SuperAmpelo is a software designed to help Vitis germplasm cataloguing, allowing to extrapolate a medium ‘mature leaf’ of each genotype (Fig. 2). Leaves with high levels of asymmetry or determining coefficient of variations among leaves of a genotype higher than 15 % are indicated by the software to be excluded from the analysis. This let us to work on symmetric leaves, so that ampelometric traits were recorded only on the right profile of a leaf, and a standard mature ‘mean leaf’ was created by the software for each genotype. The use of different measure units (cm and °) resulted in the entirely different types of scales, which had the unequal weight. The analysis data were first standardized in order to transform all characters to a comparable scale and then a principal component analysis (PCA) was performed with NTSYS-PC ver. 2.0 [14] (Fig. 3, Table 6).

Volta

Molecular Analysis

Alzey real Bellini Cardinal

Alphonse Lavallee`

Koenigin der Weingaerten

Ceresa

Muscat of Alexandria

Listan Prieto

Conegliano 218 Dalmasso VII-6

Italia Bicane

Volta Muscat of Terracina

Dalmasso XIII-11

Harslevelu

Harslevelu

Dalmasso XXIII-12

Harslevelu

Malvasia Trevigiana

Delizia di Vaprio

Sicilien

Muscat of Alexandria

Gargiulo 88086

Moscatel Rosado n° 1

Gibi x Sultanina

Gargiulo 88435

Almeria

Cardinal

Gargiulo 102011

Gargiulo 90393 ISV IxV93

Italia

Volta

Italia

Bicane

Moscat Hamburg

IxES 21

Italia

Sugraone

IxFT 87

Italia

Flame Seedless

Pirovano 100

Olivetta Barthelet

Pirovano 28

Pirovano 244

Frankenthal

Delizia di Vaprio

Pirovano 432

Bicane

I Pirovano 81

Pirovano 727 Prosperi 190

Regina x Sabalkanskoi

Italia

Sugraone

Cardinal

? (Seedless variety)

Unterkofler 50 Valsesia 54

Genomic DNA was extracted from young leaf tissue. Qiagen DNeasy Plant Mini Kit (Qiagen, Valencia, CA) was used on liquid nitrogen-frozen leaf samples, after homogenization by Qiagen Tissue Lyser (Qiagen, Valencia, CA), according to the manufacturer instruction protocol. Purified DNA was electrophoretically and spectrophoretically checked for quality and quantity, and then used as template in a PCR amplification for genotyping. Six microsatellite loci required by the EU project Genres CT96 N° 81, ‘European network for grapevine genetic resources conservation and characterization’ were amplified: VVS2 [16], VVMD5, VVMD7, VVMD27 [17, 18], and VrZAG62, VrZAG79 [19]. Two groups of three primer pairs each were carefully combined to co-amplify in a single reaction, and each forward primer was labelled with WellRED dyes, D2-PA, D3-PA or D4-PA, at the 50 end. Multiplex PCR was conducted in 20 ll reactions containing 50 ng of genomic DNA, 10 pmol of each forward and reverse primer, and QIAGEN Fast Cycling PCR Master Mix 2X (Qiagen, Hilden, Germany). The cycling profile was as following: an initial heat activation step at 95 °C for 5 min, 35 cycles of denaturation at 98 °C for 5 s, annealing at 55 °C for 30 s and extension at 68 °C for 9 s, and a final extension at 72 °C for 1 min. Amplicons were analysed on a CEQTM 10 8000 Series 11 Genetic Analysis System,

123

123

5

5

5

5

5

3 3

3

3

3

3

3

5

5

5

7

5

7

3

3

3

5 3

5

3

5

89IxU119

Alzey real

Bellini

Cardinal

Ceresa

ConeglianoPrecoce218 DalmassoVII-6

DalmassoXIII-2

DalmassoXXIII-12

DeliziaVaprio

Gargiulo102011

Gargiulo88086

Gargiulo88435

Gargiulo90393

IxES21

IxFT87

ISV IxV93

Italia

Pirovano100

Pirovano244

Pirovano432

Pirovano727 Prosperi190

Sugraone

Unterkofler50

Valsesia54

65

3

2

2

3 2

2

2

2

2

2

2

2

2

2

2

2

2

3

2

2 2

2

2

4

2

3

67

3

3

3

3 3

3

3

3

3

3

3

3

5

3

3

3

3

3

3

3 3

3

3

3

3

3

68

5

3

3

7 5

7

5

7

7

5

5

5

7

5

5

5

5

5

7

7 7

7

5

5

7

7

69

1

1

1

1 1

1

1

1

1

1

4

3

1

4

3

1

1

1

1

4 1

2

1

5

3

2

70

1

1

1

1 1

1

1

1

2

2

2

1

1

4

3

1

1

1

3

2 1

2

1

5

1

2

71

1

1

3

1 1

3

1

1

3

1

1

1

3

1

1

3

3

3

3

3 3

1

1

1

1

3

72

1

1

9

1 9

1

9

1

1

1

1

9

9

1

1

1

1

1

1

1 1

1

1

1

1

1

73

1

1

5

1 5

1

2

1

1

1

1

5

5

1

1

1

1

1

1

1 1

1

2

1

1

1

74

1

3

1

3 1

5

3

1

3

1

1

1

1

1

1

1

3

5

5

3 5

3

1

1

5

3

75

3

3

3

3 3

5

5

2

3

5

3

3

2

3

3

5

5

4

3

4 4

3

3

5

5

3

76

5

7

5

5 5

7

3

5

7

3

5

7

7

5

5

3

5

7

3

3 7

3

5

5

7

3

77

7

1

5

5 3

7

5

7

5

5

7

7

7

5

5

5

5

7

5

5 7

5

7

5

5

5

78

3

1

5

3 3

7

3

1

7

7

3

3

3

3

3

3

3

7

7

5 3

5

3

5

1

7

79

2

1

1

3 1

1

2

2

1

1

1

3

1

1

1

1

2

3

3

1 3

3

1

2

1

3

80

1

1

1

1 1

1

1

1

1

1

1

1

9

1

9

9

9

1

1

1 1

9

1

1

1

1

81-1

1

1

1

1 1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1 1

1

1

2

3

1

81-2

Table 2 Ampelographic mean values of OIV codes recorded on ‘mature leaves’ of twenty-six table grape genotypes

2

2

1

1 3

2

2

1

3

3

3

3

4

3

3

3

3

3

1

4 1

3

4

2

3

1

82

2

1

3

2 3

1

3

2

1

2

1

3

1

2

2

2

2

2

3

2 1

1

1

2

3

3

83-1

1

1

1

1 1

9

1

9

1

9

9

1

9

1

9

1

1

1

1

1 1

9

1

9

1

1

83-2

1

1

1

3 1

7

5

1

3

5

5

1

1

1

5

1

5

7

5

1 1

1

1

5

1

1

84

1

1

1

1 1

3

5

1

1

1

1

1

1

1

1

1

3

3

5

1 1

1

1

3

1

1

85

3

1

1

3 1

7

5

1

3

5

5

1

1

1

5

1

5

5

5

1 3

3

1

3

1

1

86

3

1

1

1 1

5

3

1

1

3

3

1

1

1

1

1

3

5

5

3 5

1

1

5

1

1

87

1

1

1

1 1

9

9

1

9

1

9

1

1

1

1

1

1

9

9

1 1

1

1

9

1

1

88

1

1

1

1 1

9

9

1

1

1

1

1

1

1

1

1

1

1

9

1 1

1

1

1

1

1

89

1

1

1

1 1

5

5

1

3

1

5

1

1

1

1

1

1

3

3

1 1

1

1

1

1

1

90

1

1

1

1 1

3

3

1

1

1

1

1

1

1

1

1

1

5

1

1 1

1

1

1

1

1

91

5

3

3

3 3

5

7

1

3

7

3

3

7

3

3

5

3

3

3

3 3

7

7

3

3

3

93

3

5

3

5 3

5

3

5

5

5

5

5

7

5

5

5

5

5

3

5 7

5

3

3

3

3

94

Mol Biotechnol

Mol Biotechnol Table 3 Ampelographic mean values of OIV codes extrapolated from ampelometric traits recorded on twenty-six table grape genotypes 601

602

603

604

605

606

607

608

609

610

611

612

613

614

615

616

617

89IxU119

5

7

7

9

7

7

7

3

7

9

5

5

7

3

7

3

7

Alzey real

9

9

9

9

7

9

3

3

5

7

7

7

7

5

7

3

5

Bellini

7

9

7

9

7

7

5

5

7

9

5

7

7

5

7

3

5

Cardinal n.

5

7

7

9

5

5

5

3

7

9

5

5

7

3

7

3

5

Ceresa

7

7

7

9

5

7

5

3

7

9

5

3

7

1

5

3

5

Conegliano 218

5

7

7

9

3

5

7

3

7

9

5

7

7

3

7

3

5

Dalmasso VII-6

7

7

5

9

3

3

7

5

5

5

1

7

7

3

5

3

7

Dalmasso XIII-11

5

5

5

7

5

5

7

5

7

9

1

5

7

1

5

5

5

Dalmasso XXIII-12

5

7

5

9

3

3

7

7

7

9

3

5

5

3

5

3

7

Delizia di Vaprio

5

7

7

9

3

5

5

5

5

7

5

3

7

1

5

3

5

Gargiulo 102011 Gargiulo 88086

5 5

9 5

7 5

9 9

3 3

3 3

3 5

5 3

5 5

7 9

5 3

3 3

5 5

1 1

5 5

3 3

5 3

Gargiulo 88435

5

7

7

9

3

3

7

3

7

9

5

5

7

3

5

3

5

Gargiulo 90393

7

9

9

9

3

3

5

3

7

9

5

7

7

5

7

3

5

IxES 21

7

7

7

9

7

7

5

3

7

9

5

5

7

3

5

3

5

IxFT 87

9

9

9

9

5

9

5

3

7

9

5

5

7

3

7

3

7

ISV IxV93

5

7

7

9

3

3

7

3

5

9

3

5

7

3

7

3

5

Italia

7

9

7

9

5

5

7

5

7

9

5

7

9

5

7

3

7

Pirovano 100

5

7

5

9

3

3

5

5

5

3

1

5

5

3

3

3

7

Pirovano 244

5

5

5

9

5

7

7

5

5

7

3

3

5

1

5

3

5

Pirovano 432

5

7

7

9

3

5

7

5

7

9

3

7

7

5

7

3

7

Pirovano 727

7

9

7

9

3

3

7

7

7

7

3

7

7

3

7

3

9

Prosperi 190

5

7

7

9

5

5

5

3

5

7

3

5

5

3

5

3

3

Sugraone

7

9

7

9

7

7

5

5

5

9

5

5

7

3

5

5

7

Unterkofler 50

5

5

5

9

5

5

5

3

5

7

1

5

5

3

5

3

5

Valsesia 54

7

7

7

9

3

3

7

7

7

7

3

7

7

5

7

3

9

automatically sized using a CEQ DNA Size Standard Kit 400 (Beckman 12 Coulter S.p.A., Milan, Italy), and then visually inspected and manually recorded. SSR profiles were compared to those reported in Vitis International Variety Catalogue (VIVC available at www.vivc.de) and with the Grape Microsatellite Collection (GMC available at http://meteo.iasma.it/genetica/gmc.html). To overcome the problem of correct sizing of the alleles with respect to other findings in literature, the method of alleles coding according to the list of descriptors OIV, in which the shortest allele found within the Genres 081 was arbitrarily chosen as ‘n’, was adopted. For each locus Observed (Ho) and expected (He) heterozygosities, observed number of alleles and number of different genotypes were calculated using the software POPGENE ver. 1.31 [20] (Table 7). DNA polymorphic alleles were used to create a rectangular binary matrix, where bands were scored as present (1) or absent (0) at a certain molecular weight. A similarity matrix, based on the Dice Coefficient [21], was obtained and subjected to UPGMA clustering analysis to create a

dendrogram of genetic similarity as implemented in NTSYS V2.0 software [14].

Results and Discussion Tables 2 and 3 provide an ampelographic description based on forty-seven OIV traits of twenty-one novel table grape candidate cultivars and five cultivars registered in the Italian Registry Grape Varieties and considered as reference in the present work, for a total of twenty-six genotypes. At first sight twenty-six genotypes seem a low number to extrapolate information to be transferred to a more consistent population. But the high level of heterozygosity of the grapevine is probably also one of the factors that allow a lower number of individuals than homozygous species. The small number of individuals needed to represent the genetic diversity of the cultivated grapevine pinpoints the interest in using such core collections to optimize the study of the phenotypic and genetic diversity in grapevine [13].

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Mol Biotechnol Table 4 Description of ampelometric traits recorded on twenty-six table grape genotypes Trait

Description

Le

Length of leaf

Wi

Width of leaf

Lepet

Length of leaf ? length of petiole

OP

Length of petiole

ON1 2

ON

Length of lateral vein N2

ON3 ON4

Length of lateral vein N3 Distance between petiolar point and the end of lateral vein N4

O3N4

Length of lateral vein N4

4

Length of lateral vein N5

5

ON 3

OO

Fig. 1 Ampelometric traits recorded on ‘mature leaf’

A first screening of the plant material was performed considering only the OIV primary descriptors for mature leaf. They were, however, not sufficient to distinguish among all genotypes (data not shown), consequently other OIV codes on ‘mature leaf’ were considered in the study. All genotypes showed a small–medium size of blade (OIV 65), except for IxFT87 and its parent Italia, which exhibited a large size blade. All genotypes were characterized by five lobes (OIV 68), except in the case of Gargiulo 90393 showing more than seven lobes. As expected, great variability was recorded for the degree of opening/overlapping of petiolar sinus (OIV 79), ranging from ‘very wide open petiole’ in Alzey real, Unterkofler 50 and Pirovano 100 to ‘overlapped’ in 89IxU119, Dalmasso XIII-11, Dalmasso XXIII-12, ISV IxV93, Italia and Pirovano 432, covering all intermediate stages in all the other genotypes considered. This OIV code is reported to be relevant to distinguish and identify cultivars, according to the results of data processing via discriminant analysis [3, 22]. The petiole sinus (OIV 81-2) resulted was not delimited by veins in all cases but in Alzey real and Bellini. Concerning the depth of upper lateral sinuses (OIV 94), it was recorded to be deep

123

Length of central vein N1

Lateral vein N3, distance between petiolar sinus and the end of lateral vein N4

OS

Distance between petiolar sinus and the lateral upper sinus

OI

Distance between petiolar sinus and the lateral lower sinus

a

Angle between N1 and N2 at the first bifurcation

b

Angle between N2 and N3 at the first bifurcation

c

Angle between N3 and N4

p

Width of angle of petiolar sinus

RP R2

Ratio between OP and N1 Ratio between N2 and N1

R3

Ratio between N3 and N1

R4

Ratio between N4 and N1

R5

Ratio between N5 and N1

in Dalmasso VII-6 and Gargiulo 90393, shallow medium in all the remaining genotypes. The lack of knowledge in literature about the pedigree of many table grape crosses creates difficulties in inferring general considerations based only on morphological traits. These knowledge could be of great importance since some authors [23] reported that commonly used biodiversity are phenotypic and genetic variation and the morphological changes are significantly correlated with the number changes in genetic characters. Many of the novel candidate table grape cultivars included in this paper were obtained many years ago (some of them around the beginning of last century). Consequently, information about the pedigree of some of them (7, precisely) is nowadays not available in literature. Anyway, the definition of missing pedigrees is not the real goal of our research. In this sense, Sefc et al. [4] reported that analysis of at least 25 markers is recommended for reliable pedigree studies in closely related organisms like grapevines. Pedigree reconstruction by nuclear markers can also be efficiently completed with the use of chloroplast microsatellite markers, providing information on the direction of the cross. On the contrary, based on the OIV indications, when characterizing and describing a grape genotype represent the goal of a research, six SSR markers seem to be sufficient to discriminate between

18,34

DalmassoVII-6

23,29

17,34

16,33

19,84

22,31

17,43

20,49

17,07

22,19

Italia

Pirovano100

Pirovano244

Pirovano432

Pirovano727

Prosperi190

Sugraone

Unterkofler50

Valsesia54

IXES21

25,03

23,03

Gargiulo90393

20,05

19,42

Gargiulo88435

ISV IxV93

20,89

Gargiulo88086

IxFT87

17,88

17,84

Gargiulo102011

19,14

20,94

ConeglianoPrecoce218

DeliziaVaprio

21,96

Ceresa

17,13

19,42

Cardinal

20,45

21,04

Bellini

DalmassoXXIII-12

21,91

Alzey real

DalmassoXIII-11

21,48

89IxU119

Le (cm)

21,10

17,38

19,76

17,06

23,13

19,15

16,77

16,80

20,99

18,62

22,17

21,00

20,05

19,70

17,45

19,13

18,98

19,57

15,00

17,86

19,38

20,30

18,81

18,80

20,68

21,24

Wi (cm)

30,47

22,59

26,68

24,37

28,96

25,06

24,61

22,60

28,97

26,06

33,25

32,21

28,11

25,44

25,45

24,47

27,96

25,06

22,97

24,88

27,81

33,31

32,29

26,33

30,52

25,27

Lepet (cm)

15,12

9,32

11,51

11,17

13,51

11,22

12,88

9,48

12,63

12,32

14,41

15,91

13,94

11,34

12,31

10,95

13,81

10,59

10,92

11,12

13,17

17,05

17,74

10,77

13,43

10,63

OP (cm)

15,36

13,27

15,17

13,20

15,46

13,83

11,74

13,11

16,35

13,74

18,84

16,30

14,17

14,10

13,14

13,53

14,16

14,48

12,06

13,76

14,65

16,27

14,55

15,55

17,09

14,64

ON1 (cm)

13,32

11,79

13,31

11,62

13,47

11,97

10,49

11,54

13,91

12,27

15,62

12,95

12,92

13,32

11,20

13,17

12,56

12,11

10,31

11,34

13,09

13,72

12,40

13,26

14,53

12,90

ON2 (cm)

10,15

8,38

9,90

8,62

9,95

8,60

7,99

7,70

10,19

9,29

10,94

10,37

9,99

9,93

8,70

9,97

9,52

7,99

7,21

7,41

9,63

10,08

9,31

9,18

11,04

9,48

ON3 (cm)

7,02

5,63

7,30

5,91

6,93

5,89

5,67

5,47

7,13

6,16

7,57

8,20

6,75

7,05

6,04

7,32

7,34

5,97

5,01

5,11

7,03

6,85

6,74

6,76

8,12

7,18

ON4 (cm)

5,68

4,60

6,69

4,97

5,56

5,08

4,91

4,05

6,23

5,45

6,28

7,26

5,76

6,28

5,19

5,96

6,03

5,44

4,26

3,88

6,21

6,17

5,58

5,83

7,32

6,19

O3N4 (cm)

2,54

1,80

3,67

2,15

2,65

2,58

2,36

1,35

2,81

2,56

2,96

3,94

2,84

3,30

2,78

3,57

3,41

2,79

2,07

1,38

3,25

3,34

2,89

3,60

4,17

3,17

O4N5 (cm)

1,75

1,32

0,76

1,52

1,72

1,27

0,98

1,75

1,60

1,31

2,11

1,32

1,64

1,22

1,20

1,55

1,54

0,77

1,08

1,52

1,24

1,16

1,76

1,32

0,99

1,30

OO3 (cm)

4,89

6,03

8,64

5,64

4,94

5,80

7,23

5,28

6,84

4,38

6,93

9,09

5,42

6,45

4,47

5,63

5,14

4,85

6,16

4,03

6,29

6,70

6,29

9,06

8,26

9,74

OS (cm)

4,91

6,18

7,65

6,35

4,58

4,48

6,68

4,35

6,53

3,81

8,34

8,49

4,92

5,52

4,89

5,16

6,48

4,82

5,10

3,88

6,18

7,73

6,92

7,32

8,34

8,10

OI (cm)

66,6

51,4

48,8

48,5

69,2

62,6

57,2

53,6

62,0

57,4

50,1

50,9

48,8

57,7

49,5

43,5

50,9

66,7

65,0

63,7

58,2

52,1

51,2

54,3

41,7

63,1

a (°)

56,7

41,9

47,7

39,3

59,9

56,0

49,6

47,9

48,1

48,9

44,4

44,3

41,3

44,2

43,1

49,7

48,7

49,0

57,5

51,3

42,7

38,6

41,2

47,2

42,3

58,1

b (°)

57,6

49,3

51,1

53,7

56,3

59,1

49,9

47,8

58,7

62,3

64,3

55,1

58,9

59,7

54,3

60,4

57,2

55,1

59,1

53,0

54,4

55,4

57,1

58,7

45,7

61,3

c (°)

24,8

92,2

15,4

94,5

12,4

11,9

26,8

97,0

5,9

16,2

62,1

33,7

62,6

14,4

41,5

74,8

48,9

25,4

13,9

59,2

28,6

15,3

56,1

12,4

56,1

12,0

p (°)

0,98

0,70

0,76

0,85

0,88

0,81

1,09

0,73

0,77

0,90

0,77

0,98

0,98

0,80

0,94

0,81

0,97

0,73

0,91

0,81

0,90

1,05

1,22

0,69

0,79

0,73

RP

0,87

0,89

0,88

0,88

0,87

0,87

0,90

0,88

0,85

0,90

0,83

0,79

0,91

0,95

0,85

0,98

0,89

0,84

0,86

0,83

0,90

0,85

0,85

0,85

0,85

0,88

R2

Table 5 Ampelometric traits: mean values of basic lengths, angle variables and length ratios for ‘mean leaf’ recorded on twenty-six table grape genotypes

0,66

0,63

0,65

0,65

0,65

0,62

0,68

0,59

0,62

0,68

0,58

0,64

0,71

0,71

0,66

0,74

0,67

0,55

0,60

0,54

0,66

0,62

0,64

0,59

0,66

0,65

R3

0,37

0,35

0,44

0,38

0,36

0,37

0,42

0,31

0,38

0,40

0,33

0,45

0,40

0,26

0,40

0,44

0,43

0,38

0,35

0,28

0,42

0,38

0,38

0,37

0,44

0,42

R4

0,16

0,14

0,24

0,16

0,17

0,19

0,20

0,10

0,17

0,19

0,16

0,24

0,20

0,15

0,21

0,27

0,24

0,19

0,17

0,10

0,22

0,21

0,20

0,23

0,25

0,22

R5

304,55

188,94

274,37

184,78

309,18

245,01

185,34

175,89

353,18

254,15

385,06

315,46

266,08

293,81

205,45

237,65

250,34

242,51

189,51

185,18

290,46

313,62

242,91

273,51

291,51

310,17

Leaf area (cm2)

Mol Biotechnol

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Mol Biotechnol

Fig. 2 Schematic representation of mean ‘mature leaf’ of twenty-six table grape genotypes

genotypes. We focused our attention for a first time on 13 SSR markers (data not shown). Anyway, in order to find a minimum number of elements necessary and sufficient for the production of a future core collection (the goal of the paper), we considered the publication of markers not explicitly required by the OIV to be superfluous, given that all six SSR employed in the research are well distributed on the genome and, therefore, sufficiently exhaustive in their task of differentiation of the genotypes investigated.

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In recent years ampelometric traits assume importance in grapevine morphological description since they are based on metric calculations of the most relevant characteristics of a ‘mature leaf’. The use of metric scales allows comparisons with other studies, it gives coordinates about the dispersion of data around the mean values, being an index of the accuracy of the measurements conducted. Length of main veins, distance between petiolar sinus and lateral upper and lower sinuses considered as function of

Mol Biotechnol

Fig. 3 Graphic representation of twenty-six table grape genotypes according to PRIN 1, 2 and 3 on the base of principal component analysis performed on 23 ampelometric traits. 1 = 89I x U119; 2 = Alzey real; 3 = Bellini; 4 = Cardinal; 5 = Ceresa; 6 = Conegliano 218; 7 = DalmassoVII-6; 8 = DalmassoXIII-11; 9 = DalmassoXXIII-12; 10 = Delizia di Vaprio; 11 = Gargiulo 102011;

12 = Gargiulo 88086; 13 = Gargiulo 88435; 14 = Gargiulo 90393; 15 = I X ES21; 16 = I x FT87; 17 = ISV I x V93; 18 = Italia; 19 = Pirovano 100; 20 = Pirovano 244; 21 = Pirovano 432; 22 = Pirovano727; 23 = Prosperi 190; 24 = Sugraone; 25 = Unterkofler 50; 26 = Valsesia 54

deepness of lateral sinuses, sizes of angle between veins and of petiolar sinus, and ratios between single data (Fig. 1), are often chosen as the most reliable traits when leaves are sampled correctly from the middle third of several shoots [5, 24, 25]. Based on these, a computation of twenty-three ampelometric traits was conducted by means of Superampelos 2.0. (Table 5) supported by a schematic profile of ‘mean leaf’ per genotypes (Fig. 2) in order to compare mature leaves of genotypes investigated. A ‘mean leaf area’ was also calculated, confirming the goodness of the ampelographic visualization previously performed. In particular, it was possible to establish a correspondence between leaf area in cm2 and the classes of code OIV65 relative to size of blade. Leaf area values \200 cm2 described a very small-sized, between 200 and 300 cm2 a small-sized, between 300 and 400 cm2 a medium-sized and [400 cm2 a large-sized leaf. Further, a PCA was performed on ampelometric records (Fig. 3) and Eigenvalues and Eigenvectors were calculated (Table 6). PCA was performed to reduce efficiently the information to a smaller number of dimensions. In other words, the ordination procedure allows the table grape genotypes investigated to be visualized in a spatial model

of reduced dimensions and also indicates directions of major variation. The first three vectors obtained by the ordination procedure for all traits accounted for 69.9 % of total variation. In particular, if we consider the association coefficients between the original and transformed variables ‘eigenvectors’, the first component (43.2 %) displayed differences in the behaviour of the genotypes for mean veins traits and leaf area, giving the highest positive weights. In particular, length of veins ON3, ON4 and O3N4 and leaf area had a weight around 0.900 in the determination of PRIN1. In PRIN2, which accounted for 15.9 % of total variation, the highest weights were represented by angle a (0.705), R4 and R5 (-0.642 and -0.634, respectively). PRIN3 described 10.8 % of total variation and was mainly based on variation of petiolar sinus (angle p), whose negative weight is -0.713, followed by 0.627 of angle b and by -0.602 of OO3. This analysis, in line with Santiago et al. [8], confirmed the efficiency of ampelometric traits like main veins, deepness of lateral sinuses and angles in the differentiation and characterization of table grape genotypes on the base of ‘mature leaf’ scores. Ampelometric records revealed to be more suitable, accurate and objective, thus suggesting to manage them instead

123

Mol Biotechnol Table 6 Principal component analysis: Eigenvalues, Eigenvectors and percent of variation accounted for the first three principal components on twenty-six table grape genotypes PRIN 1 Eigenvalue Variance (%)

9.93 43.2

PRIN 2 3.65

PRIN 3 2.49

15.9

10.8 69.9 0.082

Cumulative (%) Le

0.848

59.1 0.500

Wi

0.819

0.387

0.075

Lepet

0.832

0.208

-0.380 -0.462

OP

0.620

0.040

ON1

0.861

0.373

-0.144

ON2

0.877

0.238

-0.093

ON3

0.937

-0.026

-0.111

ON4

0.950

-0.139

0.011

O3N4

0.943

-0.222

0.146

O4N5

0.847

-0.382

0.252

OO3

0.108

0.469

20.602

OS

0.559

-0.246

0.353

OI

0.706

-0.257

-0.028

a

-0.293

0.705

0.472

b c

-0.215 0.264

0.438 0.388

0.627 0.191

p

-0.310

-0.267

20.713

RP

0.102

-0.223

-0.413

R2

-0.204

-0.413

0.150

R3

0.234

-0.600

0.025

R4

0.441

20.642

0.212

R5

0.591

20.634

0.315

Leaf area

0.894

0.382

0.107

Values with higher weights on the determination of PCA axes are reported in bold

of OIV ampelographic codes obtained by their conversion in discrete classes (OIV codes 601–618). As reported by Bowers et al. [26], theoretically, five unlinked markers each with five equally frequent alleles could produce over 700,000 different genotypes. In order to minimise the number of markers necessary for a reliable discrimination and identification of cultivars, the most informative loci have to be selected [4]. As reported by several authors [27–29], normally six primer pairs are sufficient for differentiating between genotypes, but closely related cultivars require larger numbers of pairs. In this case, the six couples of primers recommended by the GENRES081 project would be sufficient for differentiating the 26 genotypes. We complied with this strategy by employing in this research microsatellites as reported in Table 7: VVS2, VVMD5, VVMD7, VVMD27, VrZAG62 and VrZAG79. Since different methods of SSR analysis may result in

123

small deviations (1–2 bp) in allele size and in order to overcome the problem of allele correct sizing with respect to other findings in literature, the method of alleles coding, according to the list of descriptors OIV in which the shortest allele found within the Genres 081 was arbitrarily chosen as ‘n’, was adopted [9]. All microsatellites revealed single locus amplifications, yielding a number of alleles per locus ranging from 6 (VVMD27) to 10 (VVS2) and determining a number of different genotypes per locus ranging from 11 (VVMD7) to 18 (VVMD5). In all cases the observed heterozygosity (Ho) showed values higher than expected one (He), except for VrZAG79, being comprised between 0.78 (VrZAG79) and 0.92 (VVMD5 and VrZAG62). All microsatellites amplified homozygous loci in at least two genotypes (VVMD5 and VrZAG62) while VrZAG79 amplified a homozygous locus in six out of twenty-six genotypes. Several genotypes showed heterozygous profile at all loci, while Cardinal and Pirovano432 revealed three homozygous out of six loci. Based on microsatellite profiles, a dendrogram of genetic similarity was provided by computing the Dice Coefficient (Fig. 4). As expected, all genotypes were clearly distinguishable, confirming what extrapolated with ampelographic data. In particular, with the exception of two novel candidate cultivars—Alzey real and Bellini that behaved as out-groups, substantially, almost all parental relationships as reported in literature were evident. The first group comprised between 89IxU119 and Dalmasso XXIII12 formed at 0.38 and enclosed all genotypes sharing Italia as parent except for Prosperi 190. In particular, three genotypes, 89IxU119, Conegliano 218 and ISV IxV93 share both parents Italia x Volta and resulted in the same cluster (0.48). Similarly, Pirovano 432 and Italia showed 0.65 similarity, both having Bicane in their genetic background. Dalmasso XIII-11 and Dalmasso XXIII-12, both sharing Harslevelu as parent, showed 0.70 similarity. The second cluster grouped together Pirovano 100, Ceresa and Delizia di Vaprio, the last two sharing Muscat of Alexandria as parent and showing 0.58 similarity. For what concerns the third cluster, few speculations are possible since scarce or no information is available in literature with respect to pedigree of Gargiulo 102011, Gargiulo 88086 and Pirovano 727, the last showing 0.79 similarity with Prosperi 190, thus suggesting a possible presence of Regina, Sabalkanskoi or Italia in its pedigree. The fourth cluster grouped Cardinal together with its descendants Sugraone and Gargiulo 88435. In particular Cardinal and Sugraone revealed 0.70 similarity. In order to analyse all the set of candidate varieties with the minimum number of analyses, the microsatellite markers having the greater observed heterozygosity and discriminatory power based on the number of distinguished

Mol Biotechnol Table 7 Allele size in relative base pair distance to allele size n as coded by OIV descriptors list of twenty-six table grape genotypes at six microsatellite loci VVS2

VVMD5

VVMD7

VVMD27

VrZAG62

VrZAG79

OIV801

OIV802

OIV803

OIV804

OIV805

OIV806

89IxU119

12

28

11

15

15

23

8

22

17

29

18

Alzey real

16

20

9

13

7

7

14

14

13

29

14

22 14

Bellini Cardinal n.

30 12

34 12

5 3

15 13

9 17

17 17

8 8

14 14

15 11

19 11

2 14

24 18

Ceresa

10

26

3

17

17

17

14

22

11

19

10

14

Conegliano 218

10

28

15

17

15

17

8

22

11

17

18

20

Dalmasso VII-6

10

20

3

5

7

17

8

14

19

29

18

18

Dalmasso XIII-11

12

14

15

15

11

15

6

8

13

19

18

22 22

Dalmasso XXIII-12

12

14

3

15

15

17

6

10

19

29

18

Delizia di Vaprio

10

10

3

9

17

19

22

22

11

29

10

20

Gargiulo 102011

12

26

5

11

7

17

8

10

11

13

10

18

Gargiulo 88086

26

28

5

11

7

17

8

22

13

29

10

20

Gargiulo 88435

12

14

13

13

17

21

14

22

11

27

14

20

Gargiulo 90393

12

22

13

15

11

17

12

22

11

13

20

20

IxES 21

10

12

3

9

11

17

8

22

11

29

18

18

IxFT 87

10

26

9

11

7

11

8

14

13

29

14

18

ISV IxV93

10

28

5

15

7

15

8

14

17

17

2

18

Italia Pirovano 100

10 10

26 14

9 5

15 15

11 17

17 17

8 10

22 22

17 27

29 29

18 8

20 20

Pirovano 244

10

12

9

13

15

17

8

22

17

29

20

22

Pirovano 432

10

26

9

15

17

17

8

8

11

29

18

18

Pirovano 727

12

26

5

9

7

15

10

22

13

17

20

20

Prosperi 190

12

26

9

15

7

15

12

22

13

17

6

20

Sugraone

12

12

3

13

7

17

8

10

11

13

18

22

Unterkofler 50

10

20

3

15

19

31

8

12

19

29

10

18

Valsesia 54

10

12

7

13

15

17

6

22

17

29

18

20

H0a

0.88

HEb

0.82

0.85

0.76

0.78

0.82

0.81

nac

10

8

9

6

7

9

NDGd

14

18

11

14

14

15

a

Observed heterozygosity

b

Expected heterozygosity

c

Observed number of alleles

d

Number of different genotypes

0.92

0.81

0.88

0.92

0.78

Homozygous loci are reported in bold

genotypes and detected alleles were singularly tested to discriminate all the twenty-six genotypes (data not shown). To this, VVMD5 yielded 8 different alleles, combined in such a way that discriminated 18 genotypes, with the highest observed heterozygosity (0.92) among all loci. Anyway, to further distinguish all genotypes with the same molecular profile at the locus VVMD5, VVMD27 was efficiently tested to separate residual monomorphisms. In particular, the effectiveness of both VVMD5 and VVMD27 to distinguish and characterize table grapes cultivars is a

matter of fact, so it was included in OIV descriptors (2009) with the code OIV802 and OIV804, respectively. Indeed, Jakse et al. [30] reported locus VVMD5 to have high discriminative power in several analysed grapevines [31, 32], while Laucou et al. [33], based on criteria such as multiplexing and easy scoring, defined a minimum set of SSR markers which comprised both VVMD5 and VVMD27 and proposed them for the routine analysis of European grapevines. Similarly, This et al. [28] considered VVMD5 and VVMD27 as robust markers with stable, clear

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Mol Biotechnol Fig. 4 Dendrogram of genetic similarity based on Dice Coefficient among twenty-six table grape genotypes based on the UPGMA clustering obtained with six microsatellite loci

fragment patterns, so that they resulted to be sufficient for the discrimination of 46 table grape cultivars. The approach of using the minimum possible number of markers to differentiate genotypes is obviously related to the amount of genotypes investigated. Evidently, this number tends to increase when raising up the number of genotypes to be included in the analysis. However, considering the powerful tool represented by molecular markers, a ‘step by step’ approach could be possible when a molecular characterization is undertaken, by first testing few markers and increasing their number only if necessary. To provide a comparison of the different approaches in the description of table grape candidate cultivars and to verify the possibility of combining data generated from microsatellites and ampelometric data, matrices of cophenetic values were compared using the Mantel test. Not significant and quite low correlation between the matrices was obtained (r = -0.19, P = 0.04) after doing 1,000 random permutation with the Mxcomp procedure from NTSYS programme. The low correlation recorded suggested us to separately manage molecular and ampelometric data.

Conclusions The present work characterized twenty-one novel table grapes candidate cultivars plus five registered ones

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included as reference, by means of 47 ampelographic traits, 23 ampelometric measurements and six microsatellite loci. The final goal of the research was to analyse the possibility of reducing the number of morphological and molecular tools required for a precise and effective description of a grape genotype or cultivar diversity, preparatory to the achievement of a core collection. All the three strategies alone were proven to be effective in the distinction of all candidate cultivars. Ampelographic OIV codes from 065 to 094 for mature leaf resulted to be useful for an ‘in field’ immediate preselection of ecotypes or accessions to be enclosed in a constitution of a core collection representative of an ex-situ table grape germplasm collection which is known to be ‘land-consuming’. To this, once ‘in lab’, it is preferable to consider ampelometric traits based on metric measurements without converting them in ampelographic ones (OIV 601–618), since these last ones represent a redundancy of ampelometric codes, Surveying of ampelometric traits can reduce the number of corresponding OIV ampelographic scores to be recorded for an exhaustive and objective description by focusing mainly on veins N3, N4, on the angles between main veins and of petiolar sinus and ratios between main veins lengths, as reported by PCA. For what concerns the efficiency of microsatellites in discriminating genotypes this is largely documented in literature. Beside this, they represent a fundamental tool in table grapes biodiversity studies, in breeding programmes

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and in cultivar identification and characterization. Indeed, an approach based only on morphological traits would need a large number of individuals with numerous repetitions and several seasons, with the goal of keeping environmental variability low and identifying the most informative phenotypic characters. The effectiveness of molecular markers is confirmed by the fact that VVMD5 and VVMD27 were sufficient to distinguish all the novel table grape cultivars investigated, representing a possible ‘step by step’ approach when a molecular characterization has to be undertaken on a large number of genotypes, by first testing few markers and increasing their number only if necessary. On the other hand, this approach appears to go in the opposite direction compared to that to be taken in case a pedigree of a table grape genotype has to be provided as already mentioned above. A small number of molecular markers is certainly very little effective for the study of parental relationships between table grape genotypes, whilst easily enabling a preliminary screening to assess if two genotypes differ one from each other, thus excluding redundancies when a core collection has to be realized. This strategy represents an advisable saving of resource for a future creation of a core collection from a larger sample of more than 300 accessions and cultivars held at the ‘CRA, Research Unit of Turi (Bari—Italy)’.

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