RESEARCH

Validation Assay of p3_VvAGL11 Marker in a Wide Rangeof Genetic Background for Early Selection of Stenospermocarpyin Vitis vinifera L.

Carlo Bergamini • Maria Francesca Cardone • Angelo Anaclerio •

Rocco Perniola • Arianna Pichierri • Rosalinda Genghi • Vittorio Alba •

Lucia Rosaria Forleo • Angelo Raffaele Caputo • Cinzia Montemurro •

Antonio Blanco • Donato Antonacci

Published online: 13 March 2013

� Springer Science+Business Media New York 2013

Abstract DNA markers technology, derived from

research in molecular biology and genomics, offers great

promise for plant breeding, allowing the ‘‘molecular

breeding’’ via marker-assisted selection. Grapevine geno-

mic resources allowed, in recent years, the characterization

at molecular level of genes involved in interesting pheno-

types such as stenospermocarpic seedlessness, a trait really

appreciated by consumers. Recent studies in table grapes

revealed that the VvAGL11 gene, member of the D-lineage

MADS-box family, controls the ovule identity, and thus

potentially playing an important role in stenospermocarpy.

Intragenic markers of VvAGL11 have been found and tes-

ted for breeding purposes. In the present paper, we describe

an in deep assay on a total of 475 genotypes derived by our

own grape germplasm and seeded 9 seedless crosses F1

offspring, to evaluate and verify the ‘‘diagnostic’’ power of

VvAGL11 in marker-assisted selection. We found only

8/475 that were seeded and carried the seedless-associated

allele in the STS p3_VvAGL11. However, and most

importantly, there were no seedless varieties without such

allele. We validated the marker as a 100 % effective tool for

early negative selection of stenospermocarpy in Vitis

vinifera L. crosses.

Keywords Marker-assisted selection � Stenospermocarpy �Seedless � Grapevine breeding

Introduction

The main purpose of plant breeding is the selection of new

cultivars bearing desirable traits and better gene combina-

tions. Breeders deal with the daily challenge to reply the

continuous changes in agricultural practices and environ-

mental mutations. Genetics and molecular biotechnologies

could greatly assist plant breeders in reaching this goal. In this

aspect, molecular genetics and DNA marker technology have

the enormous potential to improve the efficiency and precision

of conventional plant breeding via marker-assisted selection

(MAS). Indeed, DNA markers can be used in genetic linkage

assays to detect allelic variation in genes underlying the

desired traits and in molecular breeding programs.

There are many important applications of MAS in plant

breeding, and, among these, the early generation marker-

assisted selection, which uses DNA markers in early gen-

erations of breeding programs. This allows breeders to

discard plants (negative selection) with undesirable gene

combination and to focus attention on a lesser number of

high-priority lines in subsequent generations [1]. This

MAS scheme is of great impact on breeding programs of

perennial species, such as grapevine, having a long-time

juvenile period, especially for phenotypes that can only be

screened in adult plants such as those affecting berries [1].

Vitis vinifera L. genomic resources have recently

increased, which will allow the identification and molecular

Carlo Bergamini, Maria Francesca Cardone authors equally

contributed to this work.

C. Bergamini � M. F. Cardone � A. Anaclerio � R. Perniola �A. Pichierri � R. Genghi � V. Alba � L. R. Forleo �A. R. Caputo � 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, Research unit for

viticulture and enology in southern Italy, Via Casamassima, 148,

70010 Turi, BA, Italy

e-mail: donato.antonacci@entecra.it

A. Anaclerio � C. Montemurro � A. Blanco

Dipartimento di Scienze del Suolo, della Piante e degli Alimenti,

Sez. Genetica e Miglioramento Genetico, Universita di Bari

‘‘Aldo Moro’’, Via Amendola 165/A, 70126 Bari, Italy

123

Mol Biotechnol (2013) 54:1021–1030

DOI 10.1007/s12033-013-9654-8

characterization of genes involved in many agronomically

important traits [1–6]. Seedlessness found in popular table

grape varieties used both for fresh and dried consumption is

one of these traits. Two kinds of seedlessness have been

described: parthenocarpic seedlessness in which the ovule

develops without fertilization, and stenospermocarpic

seedlessness, which is characterized by the seeds abortion

soon after fertilization [2]. Seedlessness is one of the pri-

mary targets of table grapes breeding programs as it is really

appreciated from consumers. Breeding programs aiming at

obtaining new seedless grape varieties are nowadays more

based on crosses between two seedless parental genotypes

followed by embryo rescue assisted by in vitro tissue culture

[7]. However, seeded 9 seedless crosses (SD 9 SL) are

still very important since most of the best table grape cul-

tivars are seeded, and the recurrent use of SL 9 SL crosses

reduces the genetic pool and can produce inbreeding

depression [8]. Thanks to the advancements in genetic

mapping studies conducted to understand the genetic

mechanism of seedlessness, MAS has been employed in

conventional breeding by markers tightly linked to the

seedlessness trait [7–11]. The most widely accepted model

proposed for the genetic control of stenospermocarpy sug-

gests the involvement of three independent and comple-

mentary recessive genes regulated by the dominant locus

seed development inhibitor (SDI) [2]. Recently, Mejia and

collaborators [1] have proposed D-lineage MADS-box gene

VvAGL11 as the major functional candidate gene for

seedlessness. P3-VvAGL11 sequence tagged site (STS)

marker, which belongs to the regulatory region of VvAGL11

and includes a (GAGA)n motif, was proposed as the most

useful marker in breeding program for seedlessness although

the same authors stated this marker needed to be tested in a

larger genetic background to assess its robustness [1].

The existence of a dominant allele at this locus and its

high heritability make stenospermocarpic seedlessness a

good candidate for MAS. Nevertheless, to ensure successful

MAS programs, QTL and marker validation are crucial.

This implies (I) confirmation of the position and effect of

the QTL by testing in different genetic backgrounds and (II)

verification of the marker usefulness by testing in important

breeding material [12]. Preliminary studies to assess the

efficiency of intragenic markers or markers tightly linked to

VvAGL11 have been reported [1, 7, 13].

Here, we present the deepest validation assay of the best

candidate VvAGL11 intragenic marker (p3-VvAGL11) on

a total of 475 genotypes including 101 grape cultivars, 198

F1 individuals of the pseudo test-cross population Ita-

lia 9 Big Perlon [14], and other 175 F1 individuals

obtained by 15 seeded 9 seedless crosses, 1 self pollina-

tion, and 6 seeded 9 seeded crosses. We confirm the tight

association of VvAGL11 with seedlessness, the usefulness

of p3_VvAGL11 marker in breeding programs for

seedlessness in terms of phenotype-genotype association,

assess false positive/negative detection rate in early nega-

tive selection, and we discuss the importance of QTLs and

markers validation strategies in MAS pipeline.

Materials and Methods

Plant Material

Marker analysis was performed on a total of 475 geno-

types. The set comprises three distinct groups. The first one

includes 101 grapevine cultivars (Table 1): among them 70

were seeded (SD), randomly chosen, and with mixed uses

(wine and table), 31 were seedless (SL), selected aiming to

include the highest number of seedless cultivars from our

own grapevine germplasm of about 1.000 unique

genotypes.

Based on their genotypes for 13 SSR markers, our

germplasm collection exhibited 272 alleles with an average

of 20.9 alleles per locus. The 101 cultivars selected for this

study represented 53 % of the total diversity and 99 % of

the restricted diversity (alleles with frequencies [0.05 %)

of our germplasm collection, which is comparable to the

diversity levels described in Le Cunff et al. [15] and

Laucou et al. [16] The cultivars are collected in the

experimental conservation vineyards (Lat. 40�57024.5400N,

Lon.17�00028.9400E) of CRA-UTV in Turi (Bari, Italy).

The second group consists of 198 F1 hybrids from the

mapping population derived by crossing the seeded cv.

Italia and the seedless cv. Big Perlon. F1 hybrids have been

grown in the field since 1999 at the Experimental Station of

the University of Bari (Italy). The population segregates for

several agriculturally important traits and was already used

by Costantini and collaborators for QTL analyses of

seedlessness [2]. Among these, 101/198 offspring were

seeded, and 97/198 were seedless.

Finally the third group under analysis includes 175 F1

hybrid plants derived from breeding programs performed in

Institutes of the Consiglio per la Ricerca e la Speriment-

azione in Agricoltura during the 1985–1992 period. Plants

were grown in the same experimental conservation vine-

yard of CRA-UTV since 2004. Parents of each Seeded 9

Seedless cross were the followings: Alphonse Lava-

llee 9 Argentina (n = 6), Alphonse Lavallee 9 Flame

Seedless (n = 1), Alphonse Lavallee 9 King Ruby

(n = 3), Alphonse Lavallee 9 Nerona (n = 3), Alphonse

Lavallee 9 Perlette (n = 19), Alphonse Lavallee 9 Perlon

(n = 12), Conegliano 218 9 Perlon (n = 2), Conegliano

199 9 Perlette (n = 3), Italia 9 Argentina (n = 2), Ita-

lia 9 Flame seedless (n = 4), Italia 9 Gargiulo 87746

(n = 1), Italia 9 Pasiga (n = 17), Italia 9 Perlette

(n = 45), Italia 9 Perlon (n = 7), Italia 9 Ruby Seedless

1022 Mol Biotechnol (2013) 54:1021–1030

123

Table 1 Varietal collection

# Variety name Seedless class p3_VvAGL11

1 Nerona 1 206/216

2 Summer royal 1 206/216

3 Thompson seedless 1 206/216

4 Beogradska 1 206/216

5 Centennial 2 206/216

6 Crimson 2 206/216

7 Autumn seedless 2 206/216

8 Melissa 2 206/216

9 Regal 2 206/216

10 Sugraone 2 206/216

11 Argentina 2 206/216

12 Patrizia 2 206/216

13 Giada 2 194/216

14 Dawn seedless 2 194/216

15 Pirovano 75 2 194/216

16 Blush seedless 2 206/216

17 Sultanina nera 2 194/216

18 Gargiulo 88086 2 206/216

19 Black opal 2 202/216

20 Carina 3 206/216

21 Apulia 3 206/216

22 Autumn royal 3 210/216

23 Ruby seedless 3 206/216

24 Serna 3 206/216

25 Sublima 3 206/216

26 Delight 3 206/216

27 Perlon 3 206/216

28 Paula 3 206/216

29 Supernova 3 206/216

30 Gargiulo 26897 3 210/216

31 IxFT87 3 206/216

32 Duraca 4 196/206

33 Gros Vert 4 194/206

34 Delizia di Vaprio 4 194/206

35 Pirovano 309 4 194/206

36 Dalmasso VII-6 4 206/206

37 Giovanna 4 194/210

38 IxV93 4 206/214

39 IxV219 4 206/214

40 Poeta Metabon 4 194/194

41 Urreti 4 214/214

42 Chasselas Lacinie 4 206/206

43 Dimiat 4 196/210

44 Pirovano 589 4 206/206

45 Gargiulo 88435 4 206/206

46 Ceresa 4 194/214

47 Pirovano 192 4 206/206

48 Angial Delzo 4 206/214

Table 1 continued

# Variety name Seedless class p3_VvAGL11

49 Rossa del Merg 4 196/206

50 Doradilla 4 210/210

51 Almeria 4 206/210

52 Raisin d’Afrique blanc 4 206/206

53 Pirovano 100 4 206/206

54 Chasselas rose 4 206/206

55 Conegliano 218 4 206/214

56 Paulsen 157 4 196/206

57 Crujidero di Spagna bianco 4 194/206

58 Duca di Magenta 4 206/216

59 Zibibbo 4 194/208

60 Olivetta Nera 4 194/206

61 Pirovano 27 4 206/206

62 Olivetta Bianca 4 194/210

63 Uva Sacra 4 206/214

64 Pirovano 205 4 196/206

65 Schiradzuoli blanc 4 206/206

66 Panse precoce 4 206/206

67 Maxia 4 206/206

68 Ciminnita 4 206/210

69 Pirovano 77 4 206/216

70 Martellata 4 196/216

71 Red globe 4 206/206

72 Christmas rose 4 206/206

73 Coarna Neagra 4 206/206

74 Pobjeda 4 196/210

75 Baresana 4 210/210

76 Dalmasso XXIII-12 4 206/206

77 Inzolia 4 206/206

78 Torbato 4 206/206

79 Pirovano 432 4 206/206

80 Emperor 4 194/206

81 Unterkofler 50 4 206/206

82 Alphonse Lavallee 4 194/206

83 Perla di Yalova 4 206/210

84 Cardinal 4 206/206

85 Fiorenza 4 206/206

86 Pirovano 2 4 194/206

87 Huevo De Gato 4 206/210

88 Bellino 4 206/206

89 Prosperi 105 4 206/216

90 Pirovano 352 4 206/206

91 Valsesia 51 4 206/206

92 Pirovano 359 4 206/210

93 Victoria 4 196/206

94 Bermestia Violacea 4 206/206

95 Tisza Istvan 4 194/206

96 Alzeireal 4 206/206

Mol Biotechnol (2013) 54:1021–1030 1023

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(n = 3). Parents of each Seeded 9 Seeded cross were the

followings: Alphonse Lavallee 9 Conegliano 199 (n = 1),

Alphonse Lavallee 9 Regina (n = 1), Conegliano 120 9

Italia (n = 1) Italia 9 Conegliano 199 (n = 21), Ita-

lia 9 Pirobella (n = 3), Italia 9 Regina (n = 19). A self-

pollination Delight 9 Delight (n = 1) was also analyzed.

Phenotypic Characterization and Seedlessness

Evaluation

Stenospermocarpic seedlessness is a complex quantitative

trait with a variable expression profile. Phenotypic char-

acterization was performed in 3 years on both quantitative

and qualitative traits. Quantitative characterization was

performed on characters correlated to berry development

and seedlessness. For each genotype, 100 berries were

randomly taken from a mixture of 3 representative clusters,

weighed, and mean berry weight (MBW) was calculated.

All seeds or seed traces from 25 berries of the mixture were

extracted, counted (seed number, SN), and weighed (total

seed fresh weight, TSFW). From these measurements,

mean seed number per berry (MSN) and mean seed fresh

weight (MSFW = TSFW/SN) were computed. MSFW was

chosen as the representative for seedlessness, and MBW

was also considered because of its previously reported

negative correlation with seedlessness [14].

Since the qualitative seedless level is the most considered

aspect by consumers, we characterized all samples in this

respect. All analyzed plants were divided in four classes: C1

for aborted and not evaluable seeds, C2 for aborted and

rudimentary seeds, C3 for complete not lignified seeds, and

C4 for lignified seeds. In this regard, it has to be taken into

account that all the seedless cultivars under analyses were

stenospermocarpic and that often it is not easy to distinguish

between the different classes as environmental conditions

could influence the expression of this trait. For this reason,

blindfolded characterization was independently performed

by two operators during three seasons (2010–2012) in ber-

ries taken from three different clusters.

DNA Extraction, Molecular Characterization,

and p3-VvAGL11 Validation Assay

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 homog-

enization 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. Molecular finger-

printing was used for both the germplasm collection and F1

hybrids to confirm the identity of individual plants, to

verify the unique genetic profile and to infer population

structure. We used thirteen SSR loci: ISV2, ISV3, ISV4,

VVS2 [17], VVMD5, VVMD7, VVMD25, VVMD27,

VVMD28, VVMD32 [18, 19], VrZAG62, VrZAG79 [20],

and VMCNG4b9 (Vitis Microsatellite Consortium). Three

or more primer pairs were carefully combined to co-

amplify in a single reaction, and each forward primer was

labeled with WellRED dyes, D2–PA, D3–PA, or D4–PA,

at the 50 end. The cycling profile was an initial heat acti-

vation 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. The

same cycling profile was used to assay VMC7f2 [21]

polymorphism on the Italia 9 Big Perlon F1 progeny.

Genetic analysis of VvAGL11 polymorphisms was

performed by genotyping all the samples with the single

tagged site (STS) marker p3_VvAGL11 defined by Mejia

et al. [1] to detect INDELs in the regulatory region on

MADSBox5 gene with some modification. In particular,

sampled DNA was subjected to PCR using the following

Table 2 Allele frequency in varietal collection

Allele 194 (176) 196 202 206 (188) 208 (190) 210 (192) 214 (196) 216 (198)

Frequency 0.09901 0.03960 0.00495 0.55941 0.00495 0.07426 0.03960 0.17822

St. Dev. 0.02101 0.01372 0.00494 0.03493 0.00494 0.01845 0.01372 0.02693

Alleles found for the p3-VvAGL11 STS marker in a grape varietal collection with frequencies and standard deviations; in brackets are reported

the corresponding sizes of previously published alleles without the M13 tail

Table 1 continued

# Variety name Seedless class p3_VvAGL11

97 Italia 4 206/206

98 Pizzutello Bianco 4 206/216

99 Michele Palieri 4 194/206

100 Prunesta 29120 4 206/206

101 Pirovano 242 4 206/206

* Afrodita 3 216/216

List of cultivars analyzed with assigned seedless class and alleles at

the p3_VvAGL11 locus. In bold are highlighted five false positive

varieties

* cv Afrodita was only qualitatively characterized and therefore not

included in statistical analysis

1024 Mol Biotechnol (2013) 54:1021–1030

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primers: VvAGL11_p3_M13_Fow 50-tgtaaaacgacggccagtC

TCCCTTTCCCTCTCCCTCT-30, VvAGL11_p3_Rev 50-AAACGCGTATCCCAATGAAG-30, which were used in a

touch-down PCR protocol together with a Wellred labeled

M13 primer 50-tgtaaaacgacggccagt-30.Amplicons were 18 nucleotides longer than expected

because of the M13 additional sequence: the use of M13

primer allows for a reduced cost of labeled primer syn-

thesis and is therefore preferred for MAS, where thousands

of samples are screened. Correspondence with literature

data are reported in Table 2.

PCR amplification was carried out on a final volume of

10 ll containing 200 ng of genomic DNA, 0.5 lM of M13

forward primer, 0.1 lM of each forward, and reverse

p3-VvAGL11 primers, and 5 ll of QIAGEN Fast Cycling

PCR Master Mix 2X. Amplicons were analyzed on a

CEQTM 8000 Series Genetic Analysis System, automati-

cally sized using a CEQ DNA Size Standard Kit 400

(Beckman Coulter S.p.A., Milan, Italy) and then visually

inspected and manually recorded. PCR thermal profile

consisted of the following: 95 �C for 10 min, 27 cycles at

annealing T� of 65.3 �C with a decrease of -0.3 �C/cycle

to reach a T� of 57 �C, plus other 22 more cycles with a

constant annealing temperature of 57 �C, and a final

extension of 15 min at 72 �C.

Data Analyses

Amplicons sizes were rounded, according to the length of

the core repeat of each analyzed SSR. The allelic fre-

quencies, Expected and Observed Heterozygosity, and the

frequencies of null alleles were calculated for the consid-

ered cultivars and statistically evaluated by the Identity 1.0

software [22]. Population structure was inferred from SSR

data using the STRUCTURE ver. 2.3.3 software [23, 24]:

this software implements a model-based (Bayesian) clus-

tering method, using genotype data consisting of unlinked

markers to identify subpopulations characterized by

determined allelic frequencies. A burn-in length of 100,000

followed by 100,000 iterations were used to estimate k

(number of subpopulations) by comparing likelihood ratios

as suggested in the Structure ver. 2.3 documentation.

The normality of each trait distribution was evaluated by

the Shapiro–Wilk test. Kruskal–Wallis test was used to

evaluate year effect. The segregation of each marker was

tested for goodness-of-fit to the expected ratios by a v2 test.

Correlations between phenotypic data were determined

using the non-parametric Spearman correlation coefficient.

Genotype-phenotype independence was assayed by v2 test

and Wilcoxon–Mann–Whitney non-parametric test.

False negative and false positive detection rates were

calculated as the number of false positive or false negative

samples over total samples belonging to the examined

phenotypic class, considering that a false negative is a

sample which does not carry the allelic variant, but

expresses the related phenotype, while a false positive has

the variant allele but does not express the phenotype.

Results and Discussion

In order to assess if the p3_VvAGL11 marker is able to

clearly discriminate between genotypes expressing or not

the stenospermocarpic trait, we decided to test the marker

in different genetic background and in a wide spectrum of

breeding materials including 101 grape cultivars, 198 F1

individuals of the cross Italia 9 Big Perlon [14], and other

175 F1 individuals obtained by 15 seeded 9 seedless

crosses, 1 selfpollination, and 6 seeded 9 seeded crosses.

Notably, phenotype–genotype association was evaluated

not only on quantitative traits related to seedlessness but

also for qualitative seedless levels.

Validation Assay on F1 Hybrids

P3_VvAGL11 STS was assayed on 198 F1 progeny derived

by the pseudo test-cross Italia (SD) 9 Big Perlon (SL).

Data previously collected on the same population showed

VMC7f2 marker as the closest to the SDl locus [2]. Indeed,

Costantini et al. [2] have reported a deep QTL analysis

proposing the 198 allele at this locus as the best molecular

marker available to predict seedlessness in the population

Italia 9 Big Perlon although its usefulness in marker-

assisted selection remained to be tested [2, 11]. In order to

compare the efficiency of p3_VvAGL11 versus VMC7f2,

we reanalyzed some of the phenotypic data and we cal-

culated phenotype-genotype association for both VMC7f2

and p3_VvAGL11 markers. Phenotypic characterization

both for qualitative seedless level, and quantitative char-

acters confirmed that this segregant population is a good

background to test the efficiency of p3_VvAGL11 and

VMC7f2 markers since 101/198 (51 %) offspring were

seeded (class C4), while 97/198 (49 %) were seedless.

Moreover, 11/97 were attributed to class C1, 33/97 to class

C2, and 53/97 to class C3. According to the Shapiro–Wilk

test, MBW showed a continuous variation and adhered to

normality only in the second of the 3 years of observation

(p = 0.0069, p = 0.159 and p = 0.005, respectively),

whereas MSFW never adhered to normality. Year effect

was tested with the Kruskal–Wallis test and found to be

significant for MBW, but not for MSFW (p \ 0.0001 and

p \ 0.088, respectively). However, non-parametric Spear-

man analysis confirmed the correlation between averaged

MSFW and MBW (q = 0.5833, p \ 0.0001). Figure 1

shows averaged MSFW (1A) and MBW (1B) values sub-

divided in the different qualitative seed classes (C1–C4)

Mol Biotechnol (2013) 54:1021–1030 1025

123

and in the two parents. MSFW was significantly different

comparing all classes in a Wilcoxon–Mann–Whitney non-

parametric test (C1 vs C2 p = 0.001, C2 vs C3 p \ 0.0001,

and C3 vs C4 p \ 0.0001). Comparing for the MBW

averages, only Class2 versus Class3 groups were found not

significantly different (C1 vs C2 p = 0.018, C2 vs C3

p = 0.714, and C3 vs C4 p \ 0.0001). However, when

assigned qualitative values of seedlessness and both

MSFW and MBW were analyzed in all samples by the non-

parametric Spearman test, a significant correlation was

found (q = 0.8262, p \ 0.0001 and q = 0.6418,

q\ 0.0001, respectively) thus testifying for the goodness

of the qualitative evaluation.

Molecular assay detected only two alleles for the marker

p3_VvAGL11 STS in the Italia (SD) 9 Big Perlon (SL)

segregant population (206 bp and 216 bp) with the parent

Italia showing homozygous genotype (allele 206/206)

while the seedless parent Big Perlon was heterozygous

206/216. Considering the use of M13 additional sequence

in primers the latter allele corresponds in size to the 198

allele previously reported to be associated with seedless-

ness [1]. As expected in a mendelian inheritance, a segre-

gation 1:1 (a:a/a:b) was observed between the two alleles

(p = 0.993), and an excellent agreement between pheno-

type and genotype was ascertained. Figure 2 reports dis-

tributions of the progeny divided as genotypes in ranked

MSFW (Fig. 2a) and in ranked MBW (Fig. 2b). Indeed all

the F1 hybrids classified as C1, C2, and C3 had the 216

allele, and none of the C4 individuals have this allele. This

means that no false negative and no false positive were

found.

The SSR marker VMC7f2 in this population showed a

similar pattern, the two parents Italia and Big Perlon being

homozygous (200/200) and heterozygous (198/200),

respectively. Segregation was found also undistorted for

this marker (p = 0.941) [2]. In addition, we also estab-

lished for both markers the false detection rate. Contrary to

what observed for p3_VvAGL11, one false positive and

three false negative cases were found for the marker

VMC7f2. In fact, one individual inherited the 198 allele

from the seedless parent Big Perlon, but classified as C4,

and three individuals, one for each class C1, C2, and C3,

lacked the allele 198. When assayed by means of the v2 test

of independence, both VMC7f2 and p3_VvAGL11 showed

strong association (p \ 0.0001) between assigned qualita-

tive levels of seedlessness and alleles 198 and 216,

respectively; also, individuals with different alleles of

VMC7f2 and p3_VvAGL11 were significantly different in

averaged MSFW and MBW (p \ 0.0001 in all four com-

binations) in a Wilcoxon–Mann–Whitney non-parametric

test. In the Italia 9 Big Perlon F1 progeny, the

p3_VvAGL11 showed 100 % efficiency in discriminating

Fig. 1 a Mean seed fresh weight (MSFW) and b Mean berry weight

(MBW) in the progeny and parents of the F1 population derived from

the cross Italia 9 Big Pearlon. c Mean seed fresh weight (MSFW)

and d mean berry weight (MBW) in the collection of 101 cultivars.

Seeded = C4; Seedless = (C1 ? C2 ? C3)

1026 Mol Biotechnol (2013) 54:1021–1030

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seeded from seedless individuals since no false positive or

false negative were detected.

Further analyses were focused to assess the discrimi-

nating power of p3_VvAGL11 in different genetic back-

grounds. We investigated a total of 175 hybrids derived

from 15 SD 9 SL, 1 self pollination, and 6 SD 9 SD

crosses. All the hybrids were characterized and classified

for qualitative seedless level: 12 belonged to the C1 rank, 47

to C2, 60 to C3, and 56 to C4. The analysis with the marker

p3_VvAGL11 STS revealed three alleles in the regulatory

region of VvAGL11, respectively, 194, 206, and 216 bp in

size. Genotypes and phenotypes were confronted: we found

that all individuals belonging to C1, C2, and C3 classes

carried the 216 allele, while only 3 out of 56 C4 individuals

showed the 216 allele, thus resulting false positives (off-

spring obtained by the crosses: Alphonse Lavallee 9 Per-

lette, Italia 9 Perlette and Italia 9 Pirobella).

Taken together, results from all the segregating proge-

nies described so far on a total of 373 F1 hybrids obtained

from crossing cultivars with different genetic backgrounds,

p3_VvAGL11 216 allele was detected in all seedless

individuals (false negative detection rate = 0 %), while all

seeded hybrids, but 3, had not the 216 allele (false positive

detection rate = 1.91 %).

Validation Assay on a Varietal Collection

Validation assay was performed on a collection of 101

cultivars selected from our own germplasm and composed

of seedless and seeded table and wine grapes for which

good quantitative data were available. The structure of this

collection was inferred from available SSR data (13

markers) using the STRUCTURE software: briefly, this

software assigns individuals to K subpopulations and pro-

duces estimated membership coefficients for each indi-

vidual in each cluster. Multiple and independent runs of

analysis by Structure for K ranging from 2 to 10 deter-

mined that the optimal number of subpopulations was

K = 4. In fact, values of the estimated log probability

reached a plateaus at K = 4 (ln Pr(X/K) = -4.660) yet

scoring slightly higher value for K = 5 (ln Pr(X/K) =

-4.620). Different values of K led to a distinct decrease in

the likelihood value. According to the instructions given in

the documentation of the software, the lowest K is probably

the most credible in order to describe the major structure in

the data (Fig. 3). Remarkably, despite the low number of

analyzed SSR, all seedless varieties with the exception of

three cultivars, were grouped in a single cluster: this result

was somehow expected since stenospermocarpy is an

unfavorable character for natural selection, but desired and

conserved by growers thanks to vegetative propagation

since its spontaneous appearance many centuries ago in a

single variety, the Thompson seedless. Common origin of

all commercial seedless varieties from this cultivar is a bias

that should be taken into account when performing an

association mapping analysis: in fact, it is not only

important to avoid false positives caused by population

structure, but also taking population structure into

account in the analysis might create false negative

results. A functional polymorphism could be considered

Fig. 2 Distribution of the F1

progeny divided as genotypes at

p3_VvAGL11 STS in ranked

MSFW (a) and ranked MBW

(b) values. Distribution of

varieties in MSFW (c) and

MBW (d) according to the

presence or absence of the 216

allele in p3_VvAGL11. Values

reported for each rank are the

median of the intervals

Mol Biotechnol (2013) 54:1021–1030 1027

123

non-significant if confounded with population structure as

is the case with the seedless table grape biased population

considered in this study. Bias in the variability and repre-

sentativeness of the considered population compared to the

whole V. vinifera diversity [15] could not be removed

because of the aforementioned unique origin of the ana-

lyzed character. All cultivars were characterized for seed-

lessness at qualitative and quantitative level in order to

assay p3-VvAGL11 efficiency. Overall results are reported

in Table 1. Thirty-one out of 101 cultivars (30.7 %) were

stenospermocarpic and the remaining 70 ones (69.3 %)

were seeded (C4 class). Among the stenospermocarpic

varieties, 12 belonged to the C3 class, 15 to C2 and 4 to C1.

According to the Shapiro–Wilk test, all the analyzed

characters did not adhere to the normal distribution.

Averaged values of MSFW was found to be correlated with

MBW by the non-parametric Spearman test with a value

(q = 0.329, p \ 0.001) even lower than the value scored in

the F1 population (q = 0.5833, p \ 0.0001). Figure 1

shows averaged MSFW (1C) and MBW (1D) values sub-

divided in the different qualitative seed classes (C1–C4).

As expected, Wilcoxon–Mann–Whitney test confirmed that

averaged MSFW was significantly different between

seedless and seeded varieties (p \ 0.0001) as were MSFW

of varieties belonging to the C1 vs C2 (p \ 0.004), C2 vs

C3 (p \ 0.009), and C3 vs C4 (p \ 0.0001) respectively.

MSFW and assigned seedlessness qualitative classes

showed a statistically significant correlation (Spearman

test, q = 0.807, p \ 0.0001). On the contrary, averaged

MBW was not significantly different even comparing

seeded versus seedless varieties (p = 0.05), and no corre-

lation was observed with assigned seedlessness qualitative

classes (q = 0.189, p = 0.064). This is in agreement with

the bias existing in the analyzed varietal collection due to

breeding for large berries in table cultivars.

Molecular validation assay on the selected cultivar

collection revealed eight different alleles for the marker

p3_VvAGL11 with size of 194, 196, 202, 206, 208, 210,

214, and 216 bp, respectively. The allelic frequencies are

reported in Table 2. Expected and observed heterozygosis

were 0.6368 and 0.6633, respectively; the estimated fre-

quency of the null alleles was -0.0162. Mejia et al. [1]

have already reported six of these alleles, while the 196-

and 202-bp alleles were not previously detected. Alleles

and genotypes of p3_VvAGL11 STS found in this popu-

lation are shown in Table 1. The relationship between

molecular and phenotypic data was statistically evaluated.

Wilcoxon–Mann–Whitney test showed significant differ-

ence in averaged MSFW between individuals showing the

216 allele and the others (p \ 0.0001), as well as the

dependence of the qualitative seedless level with the

occurrence of the 216 allele was significant in v2 test,

(p \ 0.0001). No correlation was observed for any of the

other identified alleles. Figures 2c and d show ranked

distributions of cultivars for MSFW and MBW, respec-

tively, according to the presence or absence of the 216

allele.

The allele 216 was found in all the seedless analyzed

cultivars (C1–C3). As already stated, among these, three

seedless cultivars were found grouping not in the same

73 91 92 82 86 101 37 84 34 67 38 83 77 96 32 39 100 56 95 89 81 54 98 87 93 4679 90 97 85 47 36 76 55 48 66 33 70 49 88 41 65 50 69 58 57 42 52 43 35 31

15 8 18 12 24 22 25 23 5 17 72 11 10 2 59 4 62 53 28 45 74 61 63 78 96 13 3 1 71 20 29 21 30 27 26 19 80 7 16 14 68 44 60 94 51 64 99 40 75

121 12 2 2 2 2 3 2 2 2 2 2 2 2 231 3 3 3 3 3 3 3 2 3

34 4 444

3

Varietynumber

Gen

etic

fra

ctio

n

Cluster 1 Cluster 2

Cluster 4Cluster 3

Varietynumber

Gen

etic

fra

ctio

nClass of

seedlessness

Class of seedlessness

Fig. 3 Bar plot of the genetic composition of the 101 genotypes in

the varietal collection based on SSR markers. Each column represents

a variety and it is partitioned into four segments, the length of which

represents the estimated genetic fraction in each individual of each of

the four inferred subpopulations. Boxed numbers above columns are

the qualitative seedless level of varieties carrying the 216 pb allele at

p3_VvAGL11 locus: all the others not reported belonged to the

seeded Class 4. Numbers below each column recall to varieties

sequence used in Table 1

1028 Mol Biotechnol (2013) 54:1021–1030

123

cluster, thus showing a higher genetic diversity with

respect to the Thompson s. In this regard, we could assume

that a lower membership coefficient value could reflect a

higher number of generations since the common ancestor

(Thompson s.). The existence in these cultivars of a

Linkage Disequilibrium (LD) between the p3_VvAGL11

and the seedless trait could support the causal role of

VvAGL11 gene in seedlessness, if further verified in other

stenospermocarpic seedless varieties with high genomic

diversity with respect to the Thompson s.

Five false positive samples, carrying the allele 216 but

phenotypically seeded, were found. It is noteworthy that all

five false positive samples (Varieties n. 70, 69, 58, 89, and

98) did not belong to the same subpopulation as almost

every other positive sample (Fig. 3). This might suggest a

different origin and different sequence of the 216 pb

p3_VvAGL11 allele found in these varieties compared to

the 216 pb one found in stenospermocarpic varieties. In

addition, among the remaining 65 seeded cultivars not

carrying the 216 allele as expected, four were grouped in

the cluster 1 (Varieties n. 71, 72, 80, and 59 in Fig. 3):

these varieties shared an high genetic similarity with the

Thompson s., but lacked the VvAGL11 allele of this cul-

tivar. In our opinion, this finding further emphasizes the

potential role of VvAGL11 gene in seedlessness.

The 216 allele was detected in heterozygosis with the

194, 196, 202, 206, and 210 alleles (Table 1). This result is

in agreement with the already reported partial dominant

effect of SL allele [1]. No homozygous genotype was

observed for the 216 allele with the exception of the cv.

Afrodita (class C3) which was not included in the pheno-

type–genotype correlation analysis as some quantitative

data were missing (Table 1). The homozygous genotype of

Afrodita could be the result of (I) an embryo rescue pro-

tocol applied on a cross of two seedless varieties; (II) a null

allele in heterozygosis with the 216 one; (III) a somatic

mutation leading to alleles with same size but non-identical

by descent, further propagated by breeders.

Preliminary results on 44 offspring obtained by self-

pollination of the cv. Afrodita strongly disagree with the

null allele hypothesis as only homozygous genotypes

216/216 were found (data not shown). Furthermore, we

cannot exclude that a homozygous null-allele might lead to

early embryo lethality albeit germination rates were similar

to seeds of other crosses.

The scarcity of 216/216 homozygous genotypes

observed in our collection have been also confirmed in

other literature data [1, 13]. This interesting feature

deserves further investigation. V. vinifera L. is a high-

diversity domesticated plant species characterized by high

level of heterozygosity. Nevertheless, taken into account

the common origin of seedless cultivars from Thompson

seedless, and the frequent use of SL 9 SL grape

hybridization followed by embryo rescue to increase the

frequency of seedless trait, we expected to find a higher

number of homozygous genotypes as a result of a lower

level of genomic diversity. Nevertheless apparently only

few homozygous genotypes have been further propagated.

We can speculate that the almost completely absence of

homozygote genotypes in our varietal collection could be

the results of a really early lethality or a kind of ‘‘hetero-

zygous advantage’’ at this locus: seedless heterozygous

cultivars could have better qualitative characteristic, and

thus preferred and preserved by breeders more than the

homozygous ones or could have more chances to survive to

natural selection.

Conclusions

The validation assay of VvAGL11 for seedlessness

breeding programs presented in this paper can be consid-

ered the deepest analysis of its efficiency and usefulness

since the ascertainment of the role of the VvAGL11 locus

in seedlessness [1].With respect to Mejia and collaborators

[1], we tested p3_VvAGL11 also in a different background

which is represented by a collection of 101 grape varieties.

Although they do not represent a definitive proof of the

causal role of VvAGL11 gene in seedlessness, our results

confirm the tight relationship between seedlessness and

VvAGL11 and clearly demonstrates the high potential

efficiency of the p3_VvAGL11 STS marker in breeding

programs. Taken as a whole we tested almost five hundreds

genotypes to assess the efficiency of p3_VvAGL11. The

large genetic background under study leads us to detect

some false positive cases. We ascertained 8/475 false

positives, thus corresponding to a very low false positive

detection rate of 1.68 % and, most importantly, no false

negative were found. This suggests the importance of a

detailed and deep validation assay of markers before

starting with breeding programs.

Previously, markers associated with QTLs by pre-

liminary mapping studies were directly used in MAS.

However, in recent years it has become widely accepted

that QTL and marker validation/confirmation may be

required or at least preferred as sample bias, population

size, or different background may affect QTL position, and

effect [25]. Marker validation is also necessary because of

the distance and therefore potential recombinations

between the marker and the causal mutation.

Noteworthy during early generation negative MAS, it is

more important to have a marker showing a lower false

negative detection rate than a false positive one. False

positive results in a sample that will be retained during

selection, but it will not express the phenotype and then it

will be discarded at the end of the breeding program thus

Mol Biotechnol (2013) 54:1021–1030 1029

123

leading to a useful inflation of the number of retained

individuals during early generations. It clearly appears that

p3_VvAGL11 is a really useful marker for negative

selection. However, it has to be noted that phenotype-

genotype correlation revealed that p3_VvAGL11 marker is

able to discern only those individuals that surely are not

seedless, while it does not discriminate between the dif-

ferent seedless classes. In this regard, it should be taken

into account that, from a consumer’s perspective, grapes

belonging to the C1 and C2 levels are much more desirable

than C3 and, of course, C4 levels. This last aspect com-

bined with the almost complete absence of homozygous

genotypes suggests the importance to further investigate

the other minor QTLs associated to seedlessness to better

understand the molecular basis of this trait and to find

additional markers able to discern individuals with differ-

ent seedless levels.

Acknowledgments This study was supported by Grant from Apulia

Region (PO FESR-FSE 2007-20013-Project TEGUVA cod.61/09),

the Italian Ministry of University and Research-MIUR (PON

‘‘R&C’’-2007-2013-Project ONEV- cod.00134/2011).

References

1. Mejıa, N., Soto, B., Guerrero, M., Casanueva, X., Houel, C.,

Miccono, M. E. L., et al. (2011). Molecular, genetic and tran-

scriptional evidence for a role of VvAGL11 in stenospermocarpic

seedlessness in grapevine. BMC Plant Biology, 11, 57.

2. Costantini, L., Battilana, J., Lamaj, F., Fanizza, G., & Grando, M. S.

(2008). Berry and phenology-related traits in grapevine (Vitisvinifera L.): From quantitative trait loci to underlying genes. BMCPlant Biology, 8, 38.

3. Moroldo, M., Paillard, S., Marconi, R., Fabrice, L., Canaguier,

A., Cruaud, C., et al. (2008). A physical map of the heterozygous

grapevine ‘Cabernet Sauvignon’ allows mapping candidate genes

for disease resistance. BMC Plant Biology, 8, 66.

4. Carmona, M. J., Chaıb, J., Martınez-Zapater, J. M., & Thomas,

M. R. (2008). A molecular genetic perspective of reproductive

development in grapevine. Journal of Experimental Botany, 59,

2579–2596.

5. Emanuelli, F., Battilana, J., Costantini, L., Le Cunff, L.,

Boursiquot, J. M., This, P., et al. (2010). A candidate gene

association study on muscat flavor in grapevine (Vitis viniferaL.). BMC Plant Biology, 10, 241.

6. Battilana, J., Emanuelli, F., Gambino, G., Gribaudo, I., Gasperi,

F., Boss, P. K., et al. (2011). Functional effect of grapevine

1-deoxy-D-xylulose 5-phosphate synthase substitution K284 N on

Muscat flavour formation. Journal of Experimental Botany, 62,

5497–5508.

7. Akkurt, M., Cakır, A., Shidfar, M., Celikkol, B. P., & Soylem-

ezoglu, G. (2012). Using SCC8, SCF27 and VMC7f2 markers in

grapevine breeding for seedlessness via marker assisted selection.

Genetics and Molecular Research, 11, 2288–2294.

8. Karaagac, E., Vargas, A., Andres, M., Carreno, I., Ibanez, J.,

Carreno, J., et al. (2012). Marker assisted selection for seed-

lessness in table grape breeding. Tree Genetics and Genomes, 8,

1003–1015.

9. Fatahi, R., Zamani, Z., Ebadi, A., & Mehlenbacher, S. A. (2004).

The inheritance of seedless Scc8-scar and Ssrs loci alleles in

progeny of ‘Muscat hamburg’ 9 ’bidane quermez’ grapes. IshsActa Horticulturae, 652, 329–335.

10. Adam-blondon, A., Lahogue-esnault, F., Bouquet, A., &

Boursiquot, J. (2001). Usefulness of two SCAR markers for

marker-assisted selection of seedless grapevine cultivars. Vitis,40, 147–155.

11. Cabezas, J. A., Cervera, M. T., Ruiz-Garcıa, L., Carreno, J., &

Martınez-Zapater, J. M. (2006). A genetic analysis of seed and

berry weight in grapevine. Genome, 49, 1572–1585.

12. Collard, B. C., & Mackill, D. J. (2008). Marker-assisted selection:

an approach for precision plant breeding in the twenty-first cen-

tury. Philosophical Transactions of the Royal Society of London.Series B, Biological sciences, 363, 557–572.

13. Migliaro, D., Santellani, F., Da Rold, G., Velasco R., Vezzulli, S.,

& Crespan M. (2012). Experimental assessment of molecular

markers efficiency (VvAGL11) in MAS for table grape breeding.

XXXV Word Congress of the Vine and Wine (June 2012, Izmir,

Turkey).

14. Fanizza, G., Lamaj, F., Costantini, L., Chaabane, R., & Grando,

M. S. (2005). QTL analysis for fruit yield components in table

grapes (Vitis vinifera). Theoretical and Applied Genetics, 111,

658–664.

15. Le Cunff, L., Fournier-Level, A., Laucou, V., Vezzulli, S.,

Lacombe, T., Adam-Blondon, A. F., et al. (2008). Construction of

nested genetic core collections to optimize the exploitation of

natural diversity in Vitis vinifera L. subsp. sativa. BMC PlantBiology, 8, 31.

16. Laucou, V., Lacombe, T., Dechesne, F., Siret, R., Bruno, J. P.,

Dessup, M., et al. (2011). High throughput analysis of grape

genetic diversity as a tool for germplasm collection management.

Theoretical and Applied Genetics, 122, 1233–1245.

17. Thomas, M. R., & Scott, N. S. (1993). Microsatellite repeats in

grapevine reveal DNA polymorphisms when analysed as

sequence-tagged sites (STSs). Theoretical and Applied Genetics,86, 985–990.

18. Bowers, J. E., Dangl, G. S., Vignani, R., & Meredith, C. P.

(1996). Isolation and characterization of new polymorphic simple

sequence repeat loci in grape (Vitis vinifera L.). Genome, 39,

628–633.

19. Bowers, J. E., Dangl, G. S., & Meredith, C. P. (1999). Devel-

opment and characterization of additional microsatellite DNA

markers for grape. American Journal of Enology and Viticulture,50, 243–246.

20. Sefc, K. M., Regner, F., Turetschek, E., Glossl, J., & Steinkellner,

H. (1999). Identification of microsatellite sequences in Vitisriparia and their applicability for genotyping of different Vitis

species. Genome, 42, 367–373.

21. Pellerone, F., Edwards, K., & Thomas, M. (2001). Grapevine

microsatelliterepeats: isolation, characterisation and use for

genotyping of grape germplasm from Southern Italy. Vitis, 40,

179–186.

22. Wagner, H. W., & Sefc, K. M. (1999). IDENTITY 1.0. Centre forapplied genetics. Vienna: University of Agricultural Sciences.

23. Falush, D., Stephens, M., & Pritchard, J. K. (2003). Inference of

population structure using multilocus genotype data: linked loci

and correlated allele frequencies. Genetics, 164, 1567–1587.

24. Pritchard, J. K., Stephens, M., & Donnelly, P. (2000). Inference

of population structure using multilocus genotype data. Genetics,155, 945–959.

25. Landridge, P. & Chalmers, K. J. (2005). The principle: Identifi-

cation and application of molecular markers. Biotechnology inagriculture and forestry (pp. 3–22). Heidelberg: Springer-Verlag.

1030 Mol Biotechnol (2013) 54:1021–1030

123