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Abstract

South East European (SEE) viticulture partially relies on native grapevine varieties, previously scarcely described. In order to characterize old local grapevine varieties and assess the level of synonymy and genetic diversity from SEE countries, we described and genotyped 122 accessions from Albania, Federation of Bosnia and Herzegovina (B&H), Croatia, Macedonia, Moldova, Montenegro, Republika Srpska (Bosnia and Herzegovina) and Romania on nine most commonly used microsatellite loci. As a result of the study a total of 86 different genotypes were identified. All loci were very polymorphic and a total of 96 alleles were detected, ranging from 8 to 14 alleles per locus, with an average allele number of 10.67. Overall observed heterozygosity was 0.759 and slightly lower than expected (0.789) while gene diversity per locus varied between 0.600 (VVMD27) and 0.906 (VVMD28). Eleven cases of synonymy and three of homonymy have been recorded for samples harvested from different countries. Cultivars with identical genotypes were mostly detected between neighboring countries. No clear differentiation between countries was detected although several specific alleles were detected. The integration of the obtained genetic data with ampelographic ones is very important for accurate identification of the SEE cultivars and provides a significant tool in cultivar preservation and utilization.
Vitis 52 (2), 69–76 (2013)
Molecular characterization of old local grapevine varieties from South East
European countries
M. ŽULJ MIHALJEVIĆ1), S. ŠIMON1), I. PEJIĆ1), F. CARKA2), R. SEVO2), A. KOJIĆ3), F. GAŠI3), L. TOMIĆ4), T. JOVANOVIĆ
CVETKOVIĆ4), E. MALETIĆ1), D. PREINER1), Z. BOŽINOVIĆ5), G. SAVIN6), V. CORNEA6), V. MARAŠ7), M. TOMIĆ MUGOŠA7),
M. BOTU8), A. POPA8) and K. BELESKI5)
1) University of Zagreb, Faculty of Agriculture, Zagreb, Croatia
2) Agricultural University of Tirana, Genetic Resources Center, Tirana, Albania
3) Faculty of Agriculture and Food Sciences, University of Sarajevo, Sarajevo, Bosnia and Herzegovina
4) Faculty of Agriculture, University of Banja Luka, Banja Luka, Bosnia and Herzegovina
5) Institute of Agriculture, Dept. for Viticulture and Enology, Skopje, Republic of Macedonia
6) Research and Practical Institute for Horticulture and Food Technologies, Dept. of Genetic Resources and Amelioration, Chisinau,
Moldova
7) Biotechnical Institute, University of Podgorica, Podgorica, Montenegro
8) University of Craiova, Faculty of Agriculture and Horticulture, Dept. of Horticulture and Food Science, Craiova, Romania
Correspondence to: Prof. I. PEJIĆ, University of Zagreb, Faculty of Agriculture, Svetošimunska 25, 10000 Zagreb, Croatia, Fax: +385-
1239-3631. E-mail: ipejic@agr.hr
Summary
South East European (SEE) viticulture partially
relies on native grapevine varieties, previously scarcely
described. In order to characterize old local grape-
vine varieties and assess the level of synonymy and ge-
netic diversity from SEE countries, we described and
genotyped 122 accessions from Albania, Federation of
Bosnia and Herzegovina (B&H), Croatia, Macedonia,
Moldova, Montenegro, Republika Srpska (Bosnia and
Herzegovina) and Romania on nine most commonly
used microsatellite loci. As a result of the study a total
of 86 different genotypes were identified. All loci were
very polymorphic and a total of 96 alleles were detected,
ranging from 8 to 14 alleles per locus, with an average
allele number of 10.67. Overall observed heterozygos-
ity was 0.759 and slightly lower than expected (0.789)
while gene diversity per locus varied between 0.600
(VVMD27) and 0.906 (VVMD28). Eleven cases of syn-
onymy and three of homonymy have been recorded for
samples harvested from different countries. Cultivars
with identical genotypes were mostly detected between
neighboring countries. No clear differentiation between
countries was detected although several specific alleles
were detected. The integration of the obtained genetic
data with ampelographic ones is very important for ac-
curate identification of the SEE cultivars and provides
a significant tool in cultivar preservation and utiliza-
tion.
Key words: Vitis vinifera, microsatellites, genotyping,
South East European germplasm.
Introduction
The viticulture of South East Europe (SEE) is to some
extent "personalized" due to the large number of autoch-
thonous (unique) varieties. Wine production has a signifi-
cant impact on the economy of the partners countries in-
volved in this study, but it is also tightly connected with
the history and tradition of each country. This richness of
native varieties which results in unique wines has great
potential for the future of winemaking in Europe. On the
other hand, it requires a lot of work in order to properly
maintain germplasm, perform clonal selection and ensure
high quality plant material production.
Vegetative propagation enabled conservation of culti-
vars over a long period. At the end of the 19th century, pests
and pathogens from America reached Europe (Plasmopara
viticola, Uncinula necator, Daktulosphaira vitifoliae) re-
sulting in devastation of many European vineyards and
drastically changing the diversity of grapevine (THIS et al.
2006). In the 20th century, global development of the wine
grape industry further restricted the varieties in cultivation
and led to the wide diffusion of a small number of French
cultivars (CIPRIANI et al. 2010). A progressive reduction of
the genetic diversity of crop plants is a currently occur-
ring phenomenon and "genetic erosion" especially affects
local autochthonous varieties (EL OUALKADI et al. 2011).
Many local grapevine varieties traditionally grown were
abandoned in favor of varieties more adapted to the wine
market demand and they have only recently been intro-
duced back into cultivation, in order to locally diversify the
market (CIPRIANI et al. 2010). Grapevine projects around
the world are rescuing varieties under risk of extinction
and those rescued are preserved in grapevine collections
(GARCÍA-MUÑOZ et al. 2012). During the long period of
cultivation, cultivar names were often changed because
of transliteration, substitution of local name, presence of
clones within cultivars, poor documentation and lack of
knowledge resulting in numerous cultivars that have syno-
nyms and homonyms within and among countries (CIPRIANI
et al. 2010, GARCÍA-MUÑOZ et al. 2012). The European Vitis
Database currently comprises 32,410 accessions from 35
grapevine repositories originating from 22 vine growing
nations (MAUL et al. 2012). However, from the SEE region
only data from Croatia and Moldova are available. Recent-
ly, the ampelographic and molecular characterization of lo-
cal varieties has been done in many European countries,
like Spain (SANTANA et al. 2008, VILANOVA et al. 2009, SAN-
TANA et al. 2010, MARTÌN et al 2011), Italy (SCHNEIDER et al.
2001, TORELLO MARINONI et al. 2009, CIPRIANI et al. 2010)
70 M. ŽULJ MIHALJEVIĆ et al.
Portugal (LOPES et al. 1999), Austria (SEFC et al. 1998),
Slovenia (ŠTAJNER et al. 2011). Similar characterization has
also been done recently in countries of the Mediterranean
basin like Turkey (ŞELLI et al. 2007, BOZ et al. 2011), Al-
geria (LAIADI et al. 2009), Tunisia (ZOGHLAMI et al. 2009),
Morocco (EL OUALKADI et al. 2011) and Cyprus (HVARLEVA
et al. 2005). In the last few years even larger studies have
been performed by CIPRIANI et al. 2010 and LAUCOU et al.
2011 but still South East Europe is poorly represented.
Unfortunately, in the SEE countries the level of infor-
mation on native germplasm and its present preservation
status is insufficient and fragmented. In the past years,
however, some research has been done on identifica-
tion and evaluation of genetic diversity of autochthonous
grapevine varieties (MALETIĆ et al. 1999, LADOUKAKIS et al.
2005, BENJAK et al. 2005, GHEORGHE et al.2008, STAJNER
et al. 2009, GHETEA et al. 2010). Still, for many old va-
rieties from the SEE region data and/or planting material
needed for research, breeding or growing are not available
and many of them have unknown genetic profiles. This in-
formation could be very important for managing genetic
biodiversity as well as for elucidation of genetic relation-
ship between varieties. Generally, most information is usu-
ally collected, described, analyzed or preserved following
very different methodologies which make its exchange and
use very difficult. Thus, there is a great need for regional
collaboration in grapevine germplasm analysis in order to
make a thorough inventory and an efficient regional plan
for germplasm preservation and utilization.
As a part of a regional project (see Acknowledge-
ments) the aim of this study was to perform ampelographic
and molecular characterization of some old local grapevine
varieties, traditionally grown and supposed to be native in
each SEE country. Also, this paper reports an assessment
of the level of genetic diversity and elucidates synonymous
varieties among regions.
Material and Methods
Plant material and DNA extraction:
Plant tissue for DNA extraction was collected from a total
of 122 grapevine accessions originating from seven South
East European countries. Number of accessions per coun-
try varied between 10 (Albania) and 26 (Romania). Two
entities of Bosnia and Herzegovina (Federation of B&H
and Republika Srpska) participated in the SEEDNet project
independently with 12 and 13 accessions, respectively
(Tab. 1). Young leaves from a single vine were taken during
May and June from the official germplasm collections (all
the samples from Croatia, Moldova and Romania; and two
samples ('Vranec' and 'Kratoshija') from Macedonia) and
in all other cases from in-situ vineyards. Variety identifica-
tion for sampling was performed by experienced ampelog-
raphers or viticulturists. DNA was extracted from 20 mg of
lyophilized leaf tissue according to Qiagen DNeasy Plant
Mini Kit protocol (QIAGEN, Germany).
Microsatellite analysis: Analysis was per-
formed using nine microsatellite loci: VVS2 (THOMAS and
SCOTT 1993), VVMD5, VVMD7, VVMD25, VVMD27,
VVMD28, VVMD32 (BOWERS et al. 1996, 1999), Vr-
ZAG62 and VrZAG79 (SEFC et al. 1999). This set of highly
polymorphic markers was used by the European Grape-
Gen06 consortium (http://www1.montpellier.inra.fr/grape-
gen06/accueil.php) as the standard set for the screening of
grapevine collections.
PCR amplifications were carried out in VeritiTM Ther-
mal Cycler (Applied Biosystems, Foster City, California,
USA). Two multiplex PCR reactions were carried out for
five and three of the analyzed SSRs and a singleplex for
VVMD5. The first multiplex reaction consisted of VVS2,
VVMD7, VVMD27, VrZAG62, VrZAG79 loci. In the sec-
ond multiplex VVMD25, VVMD28, VVMD32 were am-
plified.
All forward primers were labeled with 6-FAM, VIC,
PET, or NED fluorescent dyes. The reactions were pre-
pared in a final volume of 10 μL, containing 25 ng ge-
nomic DNA, 1 U Taq polymerase (Sigma-Aldrich, Ger-
many), 0.2 mM of each dNTP, 0.2μM of each forward and
reverse primer, 2X PCR buffer, 2.5 mM of MgCl2 and 1X
Q solution (Qiagen, Hilden, Germany). Singleplex was
performed in a final volume of 10 μL containing 25 ng ge-
nomic DNA, 0.5 U Taq polymerase, 0.2 mM of each dNTP,
0.2μM of VVMD5 forward and reverse primers, 2X PCR
buffer, 2.5 mM MgCl2 and 1X Q solution. The following
thermal cycling protocol was applied for all loci: precycle
94 °C for 2 min; 35 cycles of denaturation for 1 min at
94 °C, 1 min of annealing at 50 °C and 1 min extension at
72 °C; postcycle of 30 min at 72 °C and then terminated at
4 °C. Amplified products were separated using ABI3130
Genetic Analyzer (Applied Biosystems, USA) with Ge-
neScan-500 LIZTM size standard. Sizing of the fragments
was performed using GeneMapper 4.0 software (Applied
Biosystems). Amplified profiles of reference cultivars were
used for sizing the alleles of studied cultivars (THIS et al.
2004) which were afterwards coded according to Grape-
Gen06 methodology.
Ampelographic description: Ampelo-
graphic datasets were collected during 2009 and 2010 as
is specified by the Organisation Internationale da la Vigne
et du Vin (OIV 2001). Four OIV ampelographic descrip-
tors were used to complement this study: OIV-225 (berry
color), OIV-223 (berry shape), OIV-204 (bunch density)
and OIV-204 (ripening - OIV 304), out of twenty-four am-
pelographic descriptors used in this project (003, 004, 016,
065, 068, 076, 079, 084, 085, 151, 202, 203, 204, 220, 223,
225, 230, 236, 241, 235, 504, 505 and 506). Ten readings
per each descriptor were taken.
D a t a a n al y si s : Data analysis was performed
using GenAlEx 6.41 (PEAKALL and SMOUSE, 2006). The
number of alleles per locus (Na), observed heterozygosity
(Ho) and expected heterozygosity (He) were calculated for
every sampled country. Polymorphism information con-
tent (PIC) was calculated using The Excel Microsatellite
Toolkit 3.1.1. (PARK 2001). Specific alleles were detected
using software CONVERT (GLAUBITZ 2004). Allelic rich-
ness was calculated with FSTAT (GOUDET 2001). Number
of duplicates within and between sampling regions were
tested with GenAlEx 6.41. Homonyms were detected by
visual inspection. Probability of identity for unrelated gen-
Molecular characterization of old local grapevine varieties from South East European countries 71
number of alleles was detected at locus VVMD 28 (14).
Loci VVMD 25 and VVMD27 had the lowest PIC values,
0.706 and 0.705 respectively. Cumulative probability of
identity was 9.42e-12 which indicates very low probability of
two different varieties sharing the same genotype (Tab. 2).
Microsatellite markers used in this study have been prov-
en as very useful for cultivar identification. Six of them
(VVS 2, VVMD 5, VVMD 7, VVMD 27, VrZAG 62 and
VrZAG 79) are listed in the OIV primary descriptor list for
identification of grapevine cultivars. In the large study of
grape genetic diversity published by LAUCOU et al. (2011)
seven of the used markers were the same as in our study.
Analyzing 2323 accessions of Vitis vinifera subsp. sativa
they detected 12 to 25 alleles per locus and loci VVMD 28
and VVMD 32 were the most polymorphic, as in our study.
Comparing allelic richness of nine analyzed loci with a
similar study of SEFC et al. (2000) who analyzed cultivars
from geographically more distant European countries, we
find genetic diversity of South East European countries to
be relatively high.
In total 25 accessions showed to be duplicates (iden-
tical genotypes) within particular countries. Most of
them ('Lipolist', 'Dupčara', 'Žilavka', 'Nadidžar', 'Vranac',
'Kratošija', 'Plavka') consisted of accessions with identi-
cal or very similar names having identical SSR profile.
Among samples from Albania accessions 'Debine e zeze'
and 'Koteke e zeze' had identical SSR genotype. Within
samples from Macedonia accessions 'Ohridsko crno' and
'Stanushina' were found to be identical. Pairs of identical
genotypes from Moldova were 'Brează' – 'Ciorcuţă neagră'
and 'Gordin' – 'Galbenă'. Accessions 'Surac' and 'Kadarun'
from Republika Srpska as well as 'Krstač' and 'Bijela vin-
ska' from Montenegro were also found to be identical.
A subset of genotypes unique within each country of
sampling consisted of 97 accessions and was subjected
to further analysis. We searched for identical genotypes
between countries and 11 pairs of crossborder synonyms
were detected (Tab. 3). Most pairs of cultivars with identi-
cal genotype were detected among neighboring countries.
Between two entities of Bosnia and Herzegovina two pairs
otypes, probability of identity for full sibs and frequency
of null alleles were calculated using software IDENTITY4
(WAGNER AND SEFC 1999). Analysis of molecular variance
(AMOVA) was used to analyze genetic variability within
and between countries, using Arlequin 3.11 software (EX-
COFFIER et al. 2005).
Results and Discussion
Genetic diversity parameters (Tab. 1) were assessed
for the analyzed genotypes across all SEE countries. Aver-
age number of alleles per sampling country varied between
4.22 (Montenegro) and 8.67 (Romania). Small average
number of alleles as well as low values of other parameters
for Montenegro plant material can be explained through
the small number of different genotypes from this coun-
try analyzed in our study. Although initially 16 accessions
were analyzed, only six different SSR profiles were detect-
ed in Montenegro.
The first step of analysis was limited only to acces-
sions sampled within countries. Number of unique geno-
types per country varied between 37.5 % (Montenegro)
and 100 % (Croatia). Variation of allelic richness between
countries was smaller, from 3.81 (Montenegro) to 6.68
(Romania). Observed heterozygosity was smaller than the
expected one in two countries: Croatia and Moldova. For
our dataset, analysis revealed that certain alleles can be
found only among accessions from a single country, like
Romania (twelve specific alleles), Croatia (three specific
alleles) and Macedonia (three specific alleles). Information
content of a given marker may vary between cultivars from
different regions (LOPES et al. 1999) as confirmed by exist-
ence of specific alleles in our study.
All loci were very polymorphic and a total of 96 al-
leles were detected, ranging from 8 to 14 alleles per locus,
with an average allele number of 10.67. Overall observed
heterozygosity was 0.790 and slightly lower than expect-
ed (0.808) while gene diversity per locus varied between
0.600 (VVMD27) and 0.906 (VVMD28). The highest
Table 1
Grapevine genetic diversity of South East European countries
Country No of
accessions
No of
alleles
Allelic
richness HoaHebNo of unique
genotypes Specific alleles (locus, allele code)
Albania 10 5,67 5,54 0.821 0.731 9 (90%) VVMD28, N+56
B&H Federation 12 7 6,3 0.787 0.739 8 (66.6%) 0
B&H Republika Srpska 13 6,33 5,8 0.825 0.714 8 (61.5%) VVS2, N+32
Croatiac15 6,89 5,98 0.729 0.759 15 (100%) VVMD7,N+2; ZAG62, N+16; VVMD5, N ;
Macedoniac14 6,56 5,86 0.777 0.768 13 (93%) VVMD5, N+8; VVMD25, N+10; N+16;
Moldovac16 6,67 5,64 0.724 0.745 12 (81.3%) VVMD28 N+54
Montenegro 16 4,22 3,81 0.604 0.548 6 (37.5%) 0
Romaniad26 8,67 6,68 0.815 0.804 25 (96%)
VVMD7, N+26; VVMD27, N+16; VrZAG62,
N+18; VrZAG79, N+24; VVMD5, N-2; N+2;
VVMD25, N+8; VVMD28, N+2; VVMD32,
N+9; N+13; N+19; N+39
Overall 122
a Observed heterozygosity; b Expected heterozygosity; c Samples originate from official germplasm collections, address same as authors’. For Macedonia
only two samples originate from official collection. d Samples originate from official germplasm collection: Research and Development Station for
Viticulture and Oenology, Dragasani-Valcea Str. Regele, Ferdinand no. 64, Dragasani, County Valcea, 245700, Romania.
72 M. ŽULJ MIHALJEVIĆ et al.
edge and proper maintenance of grapevine germplasm. In
similar studies, the numbers of synonyms and homonyms
detected were sometimes even above 30 %. CIPRIANI et al.
(2010) found only 745 unique genotypes out of 1005 ana-
lyzed accessions, while LAUCOU et al. (2011) found 2323
different cultivars out of 3727 sativa accessions from the
Vassal collection. The results of AMOVA showed no clear
differentiation between countries (data not shown). We
also analyzed differentiation among three more distinct ge-
ographic regions (Moldova-Romania; Albania-Macedonia
and B&H-Croatia-Montenegro) and again no statistically
significant difference among them was observed.
The remaining 86 unique SSR genotypes (Tab. 4) rep-
resent the nonredundant set of regional genotypes that was
used for calculation of above mentioned genetic variation
parameters shown in Tab. 2. Only a part of OIV descrip-
tors' results (berry color, berry shape, bunch density and
of synonyms were detected. Homonyms were detected
based on visual inspection and few cases were observed.
Accessions ROU12 and ROU13 from Romania named
'Gordin' and 'Gordan' shared identical genotype but ac-
cession MDA01 named 'Gordin' from 'Moldova'showed
different SSR profile. The situation is even more com-
plex with accessions named 'Šljiva'. Two accessions from
the Federation of B&H named 'Šljiva' (BIH-FBIH05 and
BIH-FBIH06) had different genotypes and did not match
the genotype of accession named 'Šljiva' from Croatia
(CRO08). However accession BIH-RS18 which was sam-
pled as 'unknown' had the identical genotype as accession
BIH-FBIH06. Accessions 'Rezaklija' from Republika Srp-
ska and 'Razaklija' from Montenegro despite the very simi-
lar name did not have identical genotypes. It is important
to note that cultivar names were often changed during his-
tory, because of various reasons, such as lack of knowl-
Table 2
Genetic diversity parameters of the nine microsatellite markers used in this study for 86
nonredundant accessions: number of alleles (Na), observed heterozygosity (Ho), expected
heterozygosity (He), polymorphism information content (PIC), probability of identity for
unrelated genotypes (PID unrelated), probability of identity for full sibs (PID full sib) and frequency
of null alleles (F (null)
Locus Na Ho He PIC PID unrelated PID full sib F (null)
VVS 2 11 0.733 0.795 0.762 0.072 0.381 0.032
VVMD 5 12 0.812 0.873 0.854 0.032 0.326 0.030
VVMD 7 11 0.774 0.732 0.687 0.115 0.432 -0.027
VVMD 25 8 0.726 0.750 0.706 0.104 0.416 0.011
VVMD27 9 0.600 0.750 0.705 0.106 0.415 0.083
VVMD 28 14 0.906 0.899 0.884 0.021 0.309 -0.006
VVMD 32 12 0.842 0.839 0.813 0.048 0.349 -0.005
vrZAG62 9 0.849 0.790 0.760 0.072 0.385 -0.035
vrZAG79 10 0.869 0.844 0.820 0.045 0.345 -0.016
Mean: 10.67 0.790 0.808 9.42e-12 1.33e-4
Table 3
Identical genotypes (accession names with respective country codes)
1 Debine e zeze (ALB05) Koteke e zeze (ALB06)
2 Zložder (BIH-FBIH08) Bumba (CRO06)
3 Ohridsko crno (MKD01) Stanushina (MKD06)
4 Kratoshija (MKD08) Kratošija (MNE10)aKratošija stara (MNE11)
5 Vranec (MKD05) Rehuljavi vranac (MNE12) Vranac (MNE01, MNE02, MNE03, MNE05, MNE06,
MNE07, MNE08, MNE16)
6 Razaklija (MNE15) Crven valandovski drenok (MKD10)
7 Begljarka bela (MKD14) Coarnă albă (ROU01)
8 Gordin (MDA01) Galbena (MDA02) Cȃrlogancă (Crȃmpoşie veche) (ROU18)
9 Negru batut (MDA04) Bătută neagră (ROU05)
10 Turba plotnaia belaia (MDA06) Cabasma (MDA11)
11 Tamaioasa (MDA08) Tămȃioasă romȃnească (ROU17)
12 Breaza (MDA13) Ciorcuta negra (MDA16) Vulpe (ROU07)
13 Krstač (MNE09) Bijela vinska (MNE14)
14 Gordan (ROU12) Gordin (ROU13)
15 Žilavka (BIH-RS12, BIH-RS13) Žilavka(BIH-FBIH10, BIH-FBIH12)
16 Plavka (BIH-RS04, BIH-RS05) Kadarun crveni (BIH-RS17)
17 Surac (BIH-RS10) Kadarun (BIH-RS14, BIH-RS15)
18 Šljiva (BIH-FBIH06) NN(BIH-RS18)
19 Lipolist (BIH-FBIH01, BIH-FBIH04)
20 Dupčara (BIH-FBIH02, BIH-FBIH09)
21 Nadidžar (BIH-FBIH03, BIH-FBIH07)
a Duplicates (same name and country of origin).
Molecular characterization of old local grapevine varieties from South East European countries 73
Table 4
List of the 86 South East European grapevine accessions representing nonredundant genotypes, OIV descriptors and SSR profiles
Country code
and accession
number
Accession name
Berry
color
OIV-225
Berry
shape
OIV-
223
Bunch
density
OIV-
204
Ripening
OIV-304 VVS2 VVMD5 VVMD7 VVMD25 VVMD27 VVMD28 VVMD32 ssrVrZAG62 ssrVrZAG79
ALB01 Kallmet 6 4 3 57 N+10 N+30 N+10 N+18 N+18 N+18 N+4 N+28 N+6 N+14 N+30 N+30 N+15 N+37 N+14 N+20 N+6 N+6
ALB02 Sheshi i zi 6 4 5 7 N+20 N+20 N+14 N+24 N+16 N+16 N+4 N+14 N+4 N+10 N+20 N+42 N+17 N+21 N+12 N+30 N N+14
ALB03 Sheshi i bardhe 1 4 5 7 N+10 N+12 N+4 N+10 N+8 N+18 N+4 N+6 N+10 N+14 N+28 N+32 N+21 N+37 N+12 N+30 N+6 N+12
ALB04 Debine e bardhe 1 3 3 5 N+10 N+12 N+10 N+12 N+8 N+8 N+4 N+4 N+6 N+6 N+12 N+56 N+15 N+37 N+14 N+28 N+6 N+22
ALB05 Debine e zeze 6 4 3 7 N+10 N+22 N+10 N+12 N+8 N+18 N+4 N+6 N+6 N+14 N+20 N+56 N+37 N+37 N+14 N+20 N+6 N+6
ALB07 Serine e bardhe 1 3 3 5 N+20 N+28 N+10 N+10 N+8 N+12 N+20 N+28 N+6 N+6 N+28 N+30 N+27 N+37 N+14 N+14 N+20 N+22
ALB08 Pulez 1 4 7 7 N+10 N+12 N+4 N+6 N+8 N+14 N+4 N+6 N+4 N+6 N+30 N+32 N+15 N+17 N+14 N+28 N+14 N+22
ALB09 Serine e zeze 6 4 3 5 N+20 N+20 N+6 N+12 N+8 N+18 N+20 N+20 N+6 N+10 N+12 N+30 N+15 N+37 N+12 N+30 N+6 N+14
ALB10 Vloshi 3 4 5 5 N+12 N+20 N+10 N+18 N+8 N+32 N+4 N+20 N+10 N+14 N+30 N+42 N+27 N+37 N+14 N+28 N+6 N+14
BIH-FBIH04 Lipolist 1 3 5 7 N+10 N+10 N+4 N+12 N+8 N+8 N+4 N+6 N+4 N+4 N+12 N+38 N+15 N+17 N+14 N+22 N N+12
BIH-FBIH05 Šljiva 6 3 7 7 N+10 N+12 N+14 N+18 N+12 N+20 N+6 N+20 N+6 N+19 N+12 N+20 N+17 N+21 N+14 N+20 N+18 N+20
BIH-FBIH07 Nadidžar 2 4 5 7 N+18 N+28 N+10 N+10 N+8 N+14 N+4 N+6 N+4 N+10 N+42 N+42 N+21 N+23 N+22 N+28 N N+14
BIH-FBIH09 Dupčara 6 4 7 5 N+10 N+28 N+4 N+18 N+8 N+16 N+6 N+6 N+6 N+6 N+28 N+30 N+17 N+21 N+14 N+30 N+14 N+22
BIH-FBIH11 Blatina 6 3 3 7 N+20 N+28 N+4 N+4 N+8 N+16 N+4 N+28 N+6 N+14 N+28 N+42 N+27 N+29 N+14 N+30 N+8 N+22
BIH-RS02 Dalmatinka 6 2 7 5 N+10 N+22 N+4 N+16 N+8 N+18 N+6 N+6 N+6 N+6 N+28 N+44 N+15 N+37 N+14 N+14 N+6 N+20
BIH-RS04 Plavka 6 2 7 3 N+12 N+20 N+10 N+14 N+8 N+18 N+4 N+4 N+4 N+14 N+32 N+42 N+17 N+29 N+14 N+26 N N+6
BIH-RS07 Radovača 1 3 7 5 N+10 N+32 N+4 N+18 N+8 N+8 N+4 N+4 N+4 N+10 N+30 N+30 N+17 N+37 N+14 N+22 N N+14
BIH-RS08 Rezaklija 2 7 7 5 N+16 N+20 N+6 N+6 N+8 N+16 N+4 N+4 N+8 N+8 N+20 N+62 N+27 N+29 N+14 N+20 N+8 N+20
BIH-RS13 Žilavka 1 2 5 5 N+10 N+30 N+4 N+16 N+8 N+8 N+4 N+6 N+4 N+19 N+32 N+38 N+17 N+29 N+14 N+14 N+12 N+12
BIH-RS15 Kadarun 6 2 7 7 N+12 N+20 N+4 N+10 N+8 N+18 N+4 N+20 N+4 N+6 N+30 N+32 N+21 N+37 N+14 N+20 N+14 N+22
BIH-RS16 Kadarun bijeli 1 2 7 5 N+20 N+20 N+18 N+24 N+8 N+18 N+14 N+20 N+4 N+6 N+18 N+30 N+15 N+29 N+14 N+30 N N+22
BIH-RS18 Unknown 1 2 3 3 N+10 N+26 N+10 N+24 N+8 N+20 N+4 N+14 N+4 N+4 N+18 N+28 N+29 N+37 N+14 N+30 N+10 N+14
CRO01 Gustopupica ninska 6 6 5 7 N+20 N+20 N+4 N+4 N+8 N+12 N+4 N+20 N+4 N+4 N+30 N+42 N+15 N+37 N+14 N+22 N N+14
CRO02 Muškat bijeli omiški 3 4 1 5 N+10 N+26 N+6 N+10 N+18 N+20 N+14 N+14 N+4 N+19 N+28 N+52 N+29 N+37 N+12 N+30 N+10 N+18
CRO03 Vlaški crljenak 5 2 9 5 N+10 N+10 N+6 N+6 N+2 N+8 N+4 N+4 N+4 N+6 N+20 N+30 N+5 N+21 N+22 N+22 N N+12
CRO04 Bak 5 2 3 5 N+20 N+20 N+4 N+10 N+8 N+20 N+4 N+20 N+4 N+6 N+42 N+42 N+21 N+37 N+14 N+30 N+22 N+22
CRO05 Oskorušica 5 6 3 5 N+20 N+28 N+4 N+4 N+16 N+18 N+4 N+14 N+4 N+4 N+20 N+32 N+21 N+21 N+16 N+30 N+12 N+22
CRO06 Bumba bijela 1 2 7 7 N+10 N+14 N+6 N+18 N+18 N+22 N+4 N+4 N+6 N+8 N+18 N+42 N+17 N+37 N+26 N+30 N+8 N+22
CRO07 Svjetljak 1 2 5 7 N+12 N+20 n.a. n.a. N+8 N+8 N+20 N+20 N+4 N+4 N+12 N+20 N+15 N+21 N+14 N+22 N N+12
CRO08 Šljiva 5 4 3 5 N+12 N+12 N+4 N+18 n.a. n.a. N+20 N+20 N+4 N+6 N+20 N+28 N+17 N+29 N+12 N+14 N+14 N+22
CRO09 Stradunska 1 2 3 5 N+10 N+12 N+12 N+18 N+16 N+16 N+4 N+20 N+4 N+6 N+28 N+30 N+15 N+17 N+12 N+30 N+12 N+14
CRO10 Palaruša hvarska 1 2 7 3 N+28 N+28 N+4 N+6 N+16 N+18 n.a. n.a. N+6 N+6 N+32 N+62 n.a. n.a. N+16 N+30 N+12 N+22
CRO11 Bašćan 5 2 5 7 N+22 N+30 N+4 N+10 N+16 N+18 N+6 N+6 N+4 N+6 N+32 N+62 N+17 N+37 N+16 N+28 N+12 N+22
CRO12 Kamenina 6 2 7 3 N+28 N+30 N+4 N+16 n.a. n.a. N+6 N+28 N+4 N+4 N+38 N+62 N+15 N+17 N+14 N+30 n.a. n.a.
CRO13 Ošljevina 1 2 7 5 N+10 N+20 N+14 N+18 N+18 N+18 N+4 N+20 N+6 N+6 N+30 N+42 N+15 N+37 N+14 N+30 N+22 N+22
CRO14 Vrbić 1 2 3 5 N+20 N+20 N N+18 N+8 N+8 N+20 N+20 N+4 N+4 N+38 N+62 N+21 N+37 N+14 N+14 N N+18
CRO15 Volarevo 1 2 3 5 N+10 N+10 N+4 N+6 N+16 N+18 N+4 N+4 N+4 N+6 N+18 N+38 N+15 N+17 N+28 N+30 N+18 N+22
MDA03 Copciac 6 1 3 7 N+10 N+20 N+16 N+24 N+8 N+18 N+4 N+14 N+6 N+6 N+12 N+32 N+17 N+37 N+14 N+28 N+12 N+22
MDA05 Sghihara 1 2 9 7 N+10 N+10 N+6 N+24 N+16 N+18 N+4 N+4 N+4 N+10 N+32 N+44 N+17 N+37 N+30 N+30 N N+14
MDA09 Seina 6 2 5 7 N+12 N+28 N+4 N+16 N+8 N+18 N+4 N+28 N N+6 N+18 N+62 N+37 N+37 N+14 N+26 N+10 N+22
MDA10 Cianac verde 1 1 7 7 N+12 N+20 N+10 N+12 N+8 N+18 N+4 N+14 N+12 N+19 N+20 N+44 N+37 N+37 N+20 N+22 N+6 N+14
MDA11 Cabasma 1 2 5 5 N+12 N+12 N+4 N+12 N+8 N+8 N+4 N+20 N+10 N+10 N+12 N+30 N+37 N+37 N+14 N+22 N+12 N+22
MDA12 Negru de Akkertian 6 2 9 7 N+10 N+20 N+10 N+10 N+8 N+18 N+4 N+20 N+10 N+10 N+12 N+30 n.a. n.a. N+14 N+30 N+12 N+14
MDA14 Negru de Căuşeni 6 2 3 7 N+20 N+20 N+6 N+14 N+18 N+22 N+20 N+20 N+4 N+6 N+12 N+30 N+21 N+37 N+26 N+30 N N+22
MDA15 Tigvoasa 1 3 7 9 N+12 N+20 N+10 N+14 N+12 N+16 N+14 N+20 N+4 N+10 N+28 N+42 N+17 N+17 N+26 N+30 N+10 N+14
MDA17 Ciorcuţă roză 5 1 5 9 N+28 N+30 N+4 N+12 N+18 N+24 N+4 N+28 N+6 N+6 N+12 N+54 N+29 N+37 N+30 N+30 N+12 N+22
MKD02 Ohridsko belo 1 3 7 7 N+20 N+20 N+12 N+12 N+16 N+18 N+16 N+20 n.a. n.a. N+32 N+62 N+17 N+17 N+20 N+30 n.a. n.a.
MKD03 Chaush 1 7 3 5 N+12 N+20 N+16 N+24 N+8 N+18 N+14 N+20 N+4 N+4 N+18 N+42 N+29 N+37 N+14 N+22 N+12 N+14
MKD04 Belo zimsko 1 4 5 9 N+12 N+20 N+12 N+24 N+12 N+16 N+14 N+20 N+6 N+10 N+42 N+42 N+15 N+17 N+12 N+26 N+14 N+22
MKD06 Stanushina 6 2 5 7 N+12 N+20 N+10 N+18 N+18 N+18 N+4 N+20 N+6 N+14 N+28 N+30 N+15 N+37 N+20 N+30 N+6 N+6
MKD07 Begljarka crna 6 2 7 5 N+10 N+12 N+10 N+16 N+8 N+18 N+4 N+4 N+6 N+10 N+20 N+28 N+15 N+37 N+14 N+20 N+6 N+22
MKD09 Bojanka 6 2 7 5 N+16 N+28 N+4 N+12 N+8 N+12 n.a. n.a. N+6 N+8 n.a. n.a. n.a. n.a. N+14 N+14 N+6 N+22
MKD11 Crn valandovski drenok 6 7 3 9 N+22 N+28 N+8 N+14 N+20 N+24 N+6 N+14 N+4 N+4 N+42 N+52 n.a. n.a. N+14 N+30 N+20 N+22
MKD13 Manastirsko belo 1 2 3 9 N+16 N+30 N+10 N+10 N+8 N+8 N+10 N+14 N+4 N+6 N+28 N+42 N+17 N+37 N+14 N+14 N+10 N+22
MKD15 Belovina 1 2 7 5 N+10 N+10 N+12 N+16 N+8 N+18 N+4 N+6 N+4 N+10 N+12 N+18 N+29 N+37 N+14 N+30 N+14 N+14
MNE04 Lisičina 2 4 7 5 N+10 N+14 N+16 N+24 N+8 N+8 N+6 N+6 N+6 N+10 N+18 N+20 N+17 N+21 N+14 N+22 N+14 N+14
MNE11 Kratosija stara 6 4 9 5 N+10 N+20 N+4 N+14 N+16 N+18 N+4 N+4 N+4 N+6 N+32 N+42 N+21 N+29 N+26 N+30 N N+22
MNE13 Čubrica 5 4 7 5 N+10 N+20 N+14 N+24 N+8 N+18 N+4 N+14 N+4 N+6 N+20 N+42 N+29 N+37 N+14 N+26 N N+22
MNE14 Bijela vinska 4 9 5 5 N+10 N+16 N+10 N+18 N+8 N+8 N+4 N+4 N+10 N+10 N+28 N+42 N+5 N+21 N+14 N+22 N+14 N+22
MNE15 Razaklija 3 5 7 7 N+16 N+20 N+10 N+10 N+8 N+16 N+6 N+14 N+6 N+10 N+20 N+42 N+17 N+37 N+12 N+14 N+14 N+22
MNE16 Vranac 6 7 7 5 N+10 N+10 N+4 N+4 N+16 N+18 N+4 N+6 N+6 N+6 N+20 N+32 N+21 N+21 N+20 N+26 N+22 N+22
74 M. ŽULJ MIHALJEVIĆ et al.
Tab. 4 continued
Country code
and accession
number
Accession name
Berry
color
OIV-225
Berry
shape
OIV-
223
Bunch
density
OIV-
204
Ripening
OIV-304 VVS2 VVMD5 VVMD7 VVMD25 VVMD27 VVMD28 VVMD32 ssrVrZAG62 ssrVrZAG79
ROU01 Coarnă albă 1 3 9 5 N+10 N+20 N+16 N+16 N+8 N+8 N+4 N+14 N+4 N+6 N+18 N+20 N+29 N+37 N+14 N+14 N+14 N+22
ROU02 Coarnă neagră 3 3 7 5 N+14 N+20 N+14 N+14 N+16 N+18 N+8 N+14 N+4 N+10 N+18 N+28 N+21 N+39 N+14 N+26 N+10 N+14
ROU03 Ţâţa caprei albă 1 10 3 7 N+14 N+20 N+14 N+16 N+8 N+18 N+6 N+14 N+4 N+10 N+28 N+42 n.a. n.a. N+26 N+30 N+14 N+14
ROU04 Ţâţa caprei neagră 6 10 3 7 N+14 N+20 N+14 N+18 N+8 N+16 N+6 N+14 N+4 N+12 N+18 N+20 n.a. n.a. N+14 N+14 N+10 N+14
ROU05 Bătută neagră 6 2 7 5 N+10 N+20 N+10 N+10 N+8 N+18 N+4 N+14 N+10 N+10 N+18 N+20 N+17 N+17 N+14 N+30 N+12 N+14
ROU06 Negru Vârtos 6 2 9 5 N+10 N+22 N+6 N+12 N+18 N+18 N+4 N+6 N+4 N+10 N+30 N+30 n.a. n.a. N+20 N+30 N N+14
ROU07 Vulpe 6 2 3 7 N+10 N+12 N+6 N+24 N+8 N+8 N+4 N+20 N+6 N+6 N+20 N+32 N+21 N+29 N+14 N+22 N+12 N+22
ROU08 Românie 6 2 5 5 N+12 N+22 N+4 N+6 N+8 N+16 N+6 N+20 N+19 N+19 N+32 N+44 N+29 N+37 N+14 N+30 N+12 N+20
ROU09 Slaviţă 1 2 3 5 N+10 N+22 N+10 N+18 N+16 N+18 N+4 N+6 N+4 N+6 N+18 N+32 N+13 N+23 N+30 N+30 N N+22
ROU10 Om rău (Verdea) 1 7 3 7 N+20 N+20 N+12 N+12 N+8 N+18 N+14 N+20 N+6 N+6 N+12 N+20 n.a. n.a. N+14 N+30 N+6 N+22
ROU11 Fetească neagră 6 2 7 5 N+20 N+22 N+10 N+12 N+8 N+22 N+4 N+14 N+10 N+10 N+2 N+20 N+15 N+17 N+12 N+14 N+10 N+14
ROU13 Gordin 1 2 9 5 N+10 N+30 N+4 N+18 N+8 N+18 N+4 N+6 N+4 N+4 N+12 N+32 N+29 N+37 N+14 N+30 N N+12
ROU14 Teişor 1 2 3 5 N+10 N+10 N+14 N+16 N+8 N+26 N+6 N+14 N N+10 N+18 N+28 N+5 N+5 N+14 N+20 N+10 N+14
ROU15 Crâmpoşie selecţionată 1 2 7 5 N+12 N+22 N+4 N+10 N+18 N+24 N+6 N+20 N+6 N+6 N+18 N+44 N+13 N+21 N+30 N+30 N+14 N+22
ROU16 Braghină albă 1 2 3 5 N+20 N+20 N+14 N+16 N+18 N+22 N+14 N+20 N+6 N+6 N+12 N+18 n.a. n.a. N+26 N+28 N+20 N+22
ROU17 Tămâioasă românească 1 2 7 5 N+10 N+10 N+6 N+14 N+18 N+18 N+6 N+14 N+4 N+19 N+30 N+52 N+29 N+37 N+12 N+22 N+14 N+18
ROU18 Cârlogancă (Crâmpoşie veche) 1 2 7 5 N+10 N+10 N+4 N+18 N+8 N+18 N+4 N+4 N+10 N+10 N+44 N+44 N+15 N+29 N+20 N+22 N+14 N+14
ROU19 Fetească albă 1 2 7 3 N+10 N+10 N+4 N+14 N+16 N+22 N+14 N+20 N+10 N+10 N+32 N+44 N+13 N+17 N+18 N+20 N N+14
ROU20 Negru moale 6 2 7 5 N+10 N+28 N+6 N+16 N+8 N+32 N+4 N+14 N+14 N+16 N+18 N+52 N+5 N+17 N+14 N+28 N+8 N+22
ROU21 Călina 2 3 3 5 N+12 N+18 N-2 N+14 N+8 N+22 N+4 N+4 N+6 N+6 N+2 N+18 N+19 N+19 N+14 N+22 N+20 N+22
ROU22 Victoria 1 3 3 5 N+12 N+20 N+4 N+14 N+8 N+18 N+4 N+20 N+6 N+10 N+18 N+18 n.a. n.a. N+14 N+22 N+6 N+12
ROU23 Novac 6 2 5 5 N+10 N+20 N+6 N+18 N+8 N+18 N+4 N+20 N+10 N+14 N+28 N+30 N+9 N+9 N+26 N+30 N+6 N+14
ROU24 Alutus 6 2 5 5 N+10 N+20 N+2 N+16 N+8 N+18 N+4 N+14 N+6 N+14 N+18 N+28 N+9 N+21 N+26 N+28 N+6 N+20
ROU25 Vilarom 1 2 9 5 N+10 N+20 N+6 N+16 N+12 N+16 N+6 N+20 N+4 N+14 N+18 N+42 N+5 N+21 N+14 N+18 N+8 N+18
ROU26 Negru de Drăgăşani 6 2 7 5 N+20 N+22 N+2 N+6 N+8 N+18 N+6 N+20 N+4 N+4 N+28 N+30 N+15 N+37 N+14 N+30 N N+24
ALB – Albania, BIH-FBIH – Bosnia and Herzegovina Federation, BIH-RS – Bosnia and Herzegovina Republika Srpska, CRO – Croatia, MDA Moldava, MKD – Macedonia,
MNE – Montenegro, ROU - Romania.
ripening) is presented in this paper in order to provide a
basic navigation through divergence of analyzed material,
as well as their frequencies across region (Tab. 5). Berry
color is almost equally split between green yellow (41.8
%) and blue black (41.0 %). Most common berry shape
was "globose", bunch density was mostly dense to medium
dense, while regarding ripening time medium to late varie-
ties predominated.
It was interesting to take a closer look on expression
levels of ampelographic data for accessions determined by
SSRs as being synonyms or homonyms (data not shown).
In case of 'Krstač' and 'Bijela vinska' from Montenegro
that had identical SSR genotype, ampelographic results
pointed on obvious difference in berry color (green yellow
vs. grey), as well as in berry shape (narrow elipsoid vs. horn
shape). Similarly, synonym pairs 'Plavka' (BiH-RS05) and
'Kadarun crveni' (BiH-RS17) differed in berry color (blue
black vs. rose), 'Kadarun' (BiH-RS14) had blue black and
'Surac' (BiH-RS10) green yellow berry color while 'Šljiva'
(BiH-FBIH06) had blue black and accession 'NN10' (BiH-
RS05) had green yellow berry color. These findings will
require deeper ampelographic and more SSR analysis work
in order to check if the observed diversity was a result of
mutation or a human error. Three pairs of homonyms men-
tioned above had expectedly very similar phenotype what
could explain appearance of different names.
An attempt to present diversity of studied accessions
by most commonly used OIV descriptors is given in Tab. 5.
Since the ampelographic description was performed in dif-
ferent countries by different evaluators (and without ref-
erent cultivars in some cases), frequencies of levels’ of
expression of different characteristics have to be taken by
prudence. Still, they represent state of the art and provide a
rough insight in overall diversity. Ampelographic descrip-
tion of same (synonym) cultivars performed as described
above resulted in slight inconsistencies and pointed on ne-
cessity of additional characterization by molecular mark-
ers.
Conclusions
The autochthonous grapevine cultivars from South
East Europe analyzed in this study showed relatively high
level of diversity in comparison with similar studies. No
clear differentiation between countries was detected al-
though several specific alleles were identified. Detected
synonyms between neighbouring countries were mostly
unknown before, but since South East European countries
share common history, certain level of crossing between
cultivars can be expected. However, few cases of acces-
sions with identical SSR genotype but different phenotype
might be berry color mutants. The obtained results should
give a lead to ampelographers in the region to examine the
level of phenotypic (di)similarity of detected synonyms
and homonyms in more details with more independent
samples. Prospection should be continued in the region
of South East Europe to get better insight in relationships
between cultivars and to preserve the existing germplasm
for future generations. Accessions of unique and not previ-
ously published genotypes will be added to the European
Vitis Database.
Molecular characterization of old local grapevine varieties from South East European countries 75
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Acknowledgements
The project „Identification, characterization and conserva-
tion of old and autochthonous wine varieties in South Eastern
European countries“ has been conducted during 2009/10 by the
working group Fruit Crops and Vitis of the South East European
Development Network on Plant Genetic Resources (SEEDNet)
funded by the Swedish International Development Cooperation
Agency (SIDA) and the consortium has been coordinated by the
Swedish Biodiversity Centre (CBM), Swedish University of Ag-
ricultural Sciences.
Authors' contribution
K. BELESKI was the project coordinator and dealt with analy-
sis of overall ampelographic data; M. ŽULJ MIHALJEVIĆ performed
molecular characterization, preliminary data analysis and wrote
the manuscript; S. ŠIMON participated in molecular characteriza-
tion and in writing the manuscript, I. PEJIĆ supervised final data
analysis and made the concept of results and conclusions; all
other co-authors participated at national level in ampelographic
analysis and gathering plant material for DNA, as well as critical
reading of the manuscript.
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Table 5
Frequencies of some OIV characteristics for the 122 grapevine accessions presumed to be autochthonous
across South East European countries
OIV characteristic ALB BIH-FBIH BIH-RS CRO MDA MKD MNE ROU Total
n = 10 n = 12 n = 13 n =
15 n = 16 n = 14 n = 16 n = 26 n = 122
Berry color - OIV 225
1 - green yellow 40 41,7 46,2 46,7 50 42,9 6,3 53,8 41,8
2 - rose 0 16,7 15,4 0 0 0 6,3 3,8 4,9
3 - red 10 0 0 6,7 0 7,1 6,3 3,8 4,1
4 - grey 0 0 0 0 0 0 6,3 0 0,8
5 - dark red violet 0 0 0 33,3 12,5 0 12,5 0 7,4
6 - blue black 50 41,7 38,5 13,3 37,5 50 62,5 38,5 41
Berry shape - OIV 223
1 - obloid 0 0 0 0 6,3 7,1 0 0 1,6
2 - globose 0 0 84,6 73,3 87,5 50 0 73,1 50,8
3 - broad ellipsoid 30 66,7 7,7 0 6,3 14,3 6,3 15,4 16,4
4 - narrow ellipsoid 70 33,3 0 13,3 0 7,1 37,5 0 16,4
5 - cylindric 0 0 0 0 0 0 6,3 0 0,8
6 - obtuse ovoid 0 0 7,7 13,3 0 21,4 0 0 1,6
7 - ovoid 0 0 0 0 0 0 43,8 3,8 9,8
8 - obovoid 0 0 0 0 0 0 0 0 0,8
9 - horn shaped 0 0 0 0 0 0 6,3 0 1,6
10 - finger shaped 0 0 0 0 0 0 0 0 1,6
Bunch density - OIV 204
1 - very loose 0 0 0 6,7 0 0 0 0 0,8
3 - loose 50 8,3 7,7 40 12,5 0 0 34,6 19,7
5 - medium 40 50,3 23,1 20 37,5 64,3 12,5 11,5 29,5
7 - dense 10 41,7 69,2 26,7 37,5 35,7 68,8 34,6 41
9 - very dense 0 0 0 6,7 12,5 0 18,8 19,2 9
Ripening - OIV 304
1 - very early 0 0 0 0 0 0 0 0 0
3 - early 0 0 7,7 13,3 0 0 0 3,8 3,3
5 - medium 50 25 76,9 60 12,5 50 93,8 80,8 59
7 - late 50 75 15,4 26,7 68,8 21,4 6,3 15,4 32
9 - very late 0 0 0 0 18,8 28,6 0 0 5,7
76 M. ŽULJ MIHALJEVIĆ et al.
vinifera L.) Germplasm Bank of Castilla y Leon (Spain) and the va-
rieties authorized in the VQPRD areas of the region by SSR-marker
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... Other smaller winegrowing countries or regions have also genotyped their germplasm, primarily for identification of autochthonous varieties, like Austria [23], Portugal [24,25], Greece [26], Hungary [27], Transcaucasia [28], Slovenia [29,30], Bulgaria [31], Serbia [32], Bosnia, and Herzegovina [33], among others. The same has been done through international cooperation, e.g., for seven European countries [34], countries of the Iberian Peninsula [35], Southeast European countries [36], Western Balkan countries [37], and Eastern Europe [9]. ...
... Conservation of grapevine genetic resources in Croatia started about 25 years ago and six germplasm collections were established [56]. Biodiversity of Croatian grapevine germplasm has been investigated by SSRs, to a certain extent, in terms of genetic identification and variability and clarification of synonyms and homonyms [36,[57][58][59][60][61], genetic similarity to other germplasm [62], partial reconstruction of chlorotypes [53] and parentage reconstruction [63][64][65], and also partially indirectly as part of worlds' largest collections [14,15]. ...
... This resulted in the creation of a database of 2152 non-redundant genotypes, including 100 Croatian accessions previously genotyped through the GrapeGen06 project [7]. In addition, 1906 genetic profiles from publications containing shared loci [11,14,26,[29][30][31][32][33]36,37,60,[79][80][81][82][83][84][85][86][87][88][89][90][91][92][93][94] have been manually harmonized using common genotypes and added to the database for further analysis. Comparing all alleles across loci using the Excel-Microsatellite Toolkit [95], two conditions were identified: genotypes' uniqueness and/or synonymy/duplication. Accessions were considered as duplicates when they had an identical SSR profile, and assuming the existence of genotyping errors/spontaneous mutations, maximum difference of two alleles was allowed. ...
Article
Full-text available
Croatian viticulture was most extensive at the beginning of the 20th century, when about 400 varieties were in use. Autochthonous varieties are the result of spontaneous hybridization from the pre-phylloxera era and are still cultivated today on about 35 % of vineyard area, while some exist only in repositories. We present what is the most comprehensive genetic analysis of all major Croatian national repositories, with a large number of microsatellite, or simple sequence repeat (SSR) markers, and it is also the first study to apply single nucleotide polymorphism (SNP) markers. After 212 accessions were fingerprinted, 95 were classified as unique to Croatian germplasm. Genetic diversity of Croatian germplasm is rather high considering its size. SNP markers proved useful for fingerprinting but less informative and practical than SSRs. Analysis of the genetic structure showed that Croatian germplasm is predominantly part of the Balkan grape gene pool. A high number of admixed varieties and synonyms is a consequence of complex pedigrees and migrations. Parentage analysis confirmed 24 full parentages, as well as 113 half-kinships. Unexpectedly, several key genitors could not be detected within the present Croatian germplasm. The low number of reconstructed parentages (19%) points to severe genetic erosion and stresses the importance of germplasm repositories.
... Varieties Prokupac, Vranac, Krstač, Žilavka, Plavac Mali, and Istrian Malvasia are internationally recognized and under these names are included in the VIVC catalogue and many collections of grapevine. The unique DNA profile and authenticity of these varieties, both in the set of international varieties [45, 47 -51] and using other SSR markers [1,22,26,32,33,52,53] has been confirmed. ...
... Complimentary Contributor Copy INDEX A acetaldehyde, 143, 148, 177 acetic acid, 21, 22, 23, 142, 146, 149, 154, 156, 166, 168, 182, 183 acid, xi, 7, 20, 22, 23, 25, 26, 50, 52, 53, 54, 55, 57, 59, 71, 77, 88, 94, 97, 101, 102, 107, 108, 112, 114, 120, 121, 124, 135, 142, 146, 147, 148, 154, 170, 174, 175, 181, 182, 190, 191 acid detergent fibre, 95, 114, 120, 121 acid detergent lignin, xi, 112, 114, 120, 121 acidic, 145, 188 acidity, 13, 46, 143, 146, 147, 148, 149, 154, 172 agriculture, x, 68, 69, 86, 130 air temperature, 95, 114 alcohol production, 190 aldehydes, 157, 158 ampelographic, vii, ix, 2, 4, 11, 12, 13, 27, 29, 30, 34, 44, 45, 47, 48, 60, 61 ampelographic characterization, 2, 34, 44, 61 anthocyanin, 12, 20, 23, 24, 39, 48, 53, 55, 57, 58, 189 Complimentary Contributor Copy Index 194 bioavailability, 34,63 biochemistry,135 biodiversity,27,45,128,133,167 biogeography,vi,xi,127,128,129,130,132,159,161,162,164,166,169,170,172,178,180 biological activity,42 biomass,89,125,126 Bosnia,3,4,5,8,11,40,48 Bulgaria,3,7,69,105,112,113,116,119,122,123,125 C Cabernet franc, ix,x,41,63,68,70,75,76,77,103,104,111,114 Cabernet Sauvignon,ix,x,18,37,38,39,55,56,58,59,61,63,68,70,75,76,77,79,84,92,94,99,100,103,104,119,170,176 calibration,82,83,87 Canaiolo nero,ix,x,68,70,75,77,112,114,118 carbohydrates,93 carbon,80,107,131,142,151,154,155 carbon atoms,155 carbon dioxide,131,142,151 carbon tetrachloride,107 carboxylic acid,94 Carignan noir,ix,x,68,70,74,75,76,77,112 cell biology,135 cellulose,97,150 characterization,v,vii,viii,ix,1,2,11,14,15,19,20,26,27,28,29,30,31,32,34,36,38,43,44,46,61,62,86,105,108,122,161,163,165,166,168,172,177,180,182,183,188,190 cheese,130,154 chemical characteristics,vii,ix,4,44,59 chemical characterization,vii,viii,2,20,26,40,44,60 chemical composition,vii,ix,x,19,20,27,42,53,54,64,68,69,72,75,87,92,94,98,99,100,101,106,111,112,113,115,116,117,118,120,121,123,124,125,126 chemical properties,27,106 chemical reactions,156 classification,16,39,44,51,72,84 climate,viii,1,3,9,63,131,133,140,147,148,162 climate change,viii,2,3 climatic factors,132 clonal characterization,44,52 clonal selection,v,ix,17,43,44,46,49,52,60,62 food industry,28 food production,162 forage,x,68,69,71,79,86,87,88,89,92,106,119,124 forage crops,68 formation,119,177,183,185,189 France,45,166 fruits,40,93 M Mali,vii,viii,2,9,11,12,16,17,18,20,22,23,24,25,26 Malvasia bianca di Candia,x,112,114,116 Malvazjia Istarska,9 management,63,133,144 mechanical properties,50 Mediterranean,x,2,4,31,86,89,92,93,126 Mediterranean countries,x,92 metabolism,129,145,153,154,157,175,184 metabolites,19,125,141,142,143,147,151,155,191 microbial communities,viii,xi,128,129,130 microbial community,185,191 microclimate,131,133,140,142 microorganisms,xi,128,129,130,132,141,160,178 Middle East,4,5,6,44,93 molecular caracterisation,14 molecular data,47 Complimentary Contributor Copy Index ...
Chapter
Biogeography is the study of the distribution of species over space and time and aims to understand where, why, and at what abundance organisms live. Revealing the diversity and distribution pattern of populations and communities at multiple spatial scales is thus a central issue in ecology. Recent biogeographic studies based on genetic technologies revealed that microorganisms are not randomly distributed over space and time, showing that their distribution is systematically heterogeneous and structured, revealing specific patterns of microbial distribution. In this context, the study of microbial communities associated with vineyards points to the existence of patterns of microbial distribution across viticultural areas, suggesting a microbiological component of the terroir concept. In the light of this knowledge, the composition of the yeast flora present on grapes, besides representing a long-term known factor of wine quality tends to be presently seen as a potential factor of wine typicality. To assess grape yeast diversity and to understand the ecological and geographical factors shaping the yeast communities and populations composition is of great importance for modern oenology. In this chapter we present on overview of the research developed in this scope.
... Simple sequence repeats (SSR) or short tandem repeats (STR) markers, also known as microsatellites, have been widely used since the early 1990s [6] and are nowadays considered to be some of the best methods for determining cultivar identity. Due to their high polymorphism, microsatellite markers have significantly improved the robustness of DNA profiling in parentage analysis [7][8][9][10][11] and in the molecular characterization of grape cultivars [12][13][14][15][16][17][18][19][20][21]. ...
... This scenario is evident, with no exception, for all the Bulgarian varieties studied, Table S4. Greek (1)(2)(3)(4)(5)(6)(7)(8) and Bulgarian (9)(10)(11)(12)(13)(14)(15)(16)(17) populations-varieties used in the present study. Letters G and B in parentheses stand for Greek and Bulgarian, respectively, Table S5. ...
Article
Full-text available
The aim of this study was to estimate the genetic diversity of Greek and Bulgarian grapevine varieties with the use of microsatellite markers. The studied samples were collected from various productive vineyards, consisting of eight Greek and nine Bulgarian native varieties. In order to create a genetic profile for each sample, a multiplex PCR reaction method was used amplifying simultaneously seven microsatellite loci. Statistical analysis of data showed that there was a high degree of genetic heterogeneity among most of the varieties studied, highlighting the discriminative power of the chosen set of markers. Moreover, the synonymy of (I) Greek Pamid and Bulgarian Pamid and (II) Greek Zoumiatiko and Bulgarian Dimyat was suggested, as each variety pair had identical allele profiles in all loci examined. Regarding the Greek Mavrud and Bulgarian Mavrud varieties, there was a close genetic relationship between them, however, they did not share common alleles in all microsatellite loci and, therefore, should not be characterized as synonyms. On the other hand, Greek and Bulgarian Keratsouda, which were supposed to be common varieties, were found to be genetically different, supporting that these two varieties should be considered as homonyms. Despite the genotypic assay performed herein, we believe that additional molecular work is needed for the efficient management of Greek and Bulgarian grapevine genepools, as well as to safely suggest any synonym or homonym annotation.
... Since many research groups around the world have become interested in the microsatellite genotyping of vines, a large number of these markers have been developed (Bowers et al., 1996;Bowers et al., 1999;Sefc et al., 1999;Adam-Blondon et al., 2004;Arroyo-Garcia and Martinez-Zapater, 2004;Di Gaspero et al., 2005;Merdinoglu et al., 2005;Goto-Yamamoto et al., 2006). A defined set of six (VVS2, VVMD5, VVMD7, VVMD27, VrZAG62 and VrZAG7) or nine (the previous six combined with VVMD32, VVMD36 and VVMD25) highly polymorphic microsatellite markers is commonly used in grapevine genotyping studies, usually with the purpose of determining genetic variability between European grape varieties, which are highly polymorphic (Sefc et al., 2001;Žulj Mihaljević et al., 2013). The purpose of this study was to carry out the ampelographic characterisation, evaluation and microsatellite profiling of 30 vine varieties to find potential synonyms within this group, as well as to compare the obtained profiles with the available DNA profiles of grapevines from other regions in Europe. ...
Article
Full-text available
Characterisations of thirty grapevine varieties (Vitis vinifera L.) from the experimental vineyard ‘Radmilovac’ were conducted using a large number of OIV descriptors and eight highly polymorphic microsatellite loci. The ampelographic description contained 45 features. Molecular characterisation of selected microsatellite loci was performed using capillary electrophoresis fragment analysis. Dendrograms based on ampelographic and genetic data resulted in three groups of varieties. Qualitative ampelographic characteristics tended to manifest significant differences. The most common deviation among varieties within the group was in the characteristic OIV 051 (colouration of the upper side of a young leaf). Genetic characterisation of SSR markers through analyses of a large number of varieties contributes to better organisation of grapevine collections and simpler identification of varieties, as well as data exchange. When identifying the varieties, the results of the DNA analysis should be combined with the ampelographic descriptors, in order to select grapevine varieties with desirable viticultural and oenological traits. Integration of the obtained genetic data with the ampelographic data is of utmost importance for accurate identification of the varieties and offers a significant means for the preservation and use of the varieties.
... This is the first study to assess the genetic diversity and relationships among 23 wild Chinese Vitis species/cultivars using this powerful microsatellite technique. The nine SSR markers selected in this study, which are high in polymorphisms, have been used by the European GrapeGen06 consortium (Maul et al., 2012) and have been used frequently to identify grape cultivars (Li et al., 2018;Mihaljevic et al., 2013;This et al., 2004). Internationally, France, Germany, Italy, and other countries have used the nine SSR markers to establish a molecular database of grape cultivars (Maul and T€ opfer, 2015), providing an inquiry service for grape research workers. ...
Article
Full-text available
Chinese wild Vitis is a useful gene source for resistance to biotic and abiotic stresses, although there is little research on its genetic diversity and structure. In this study, nine simple sequence repeat (SSR) markers were used to assess the genetic diversity and genetic structure among 100 Vitis materials. These materials included 77 indigenous accessions representing 23 of 38 wild Vitis species/cultivars in China, 18 V. vinifera cultivars, and the five North American species V. aestivalis , V. girdiana , V. monticola , V. acerifolia , and V . riparia . The SSR loci used in this study for establishing an international database ( Vitis International Variety Catalogue) revealed a total of 186 alleles in 100 Vitis accessions. The mean values for the gene diversity (GD) and polymorphism information content (PIC) per locus were 0.91 and 0.90, respectively, which indicates that the discriminatory power of the markers is high. Based on the genetic distance data, the 100 Vitis accessions were divided into five primary clusters by cluster analysis, and five populations by structure analysis; these results indicate these Chinese wild grapes were more genetically close to European grapes than to North American species. In addition, the clustering patterns of most accessions correlated with the geographic distribution. An analysis of molecular variance (AMOVA) revealed that 3.28%, 3.27%, and 93.46% of the variance occurred between populations, between individuals within populations, and between individuals within the entire population, respectively. In addition, we identified three previously undescribed accessions (Wuzhi-1, MZL-5, and MZL-6) by cluster analysis. Our results reveal a high level of genetic diversity and variability in Vitis from China, which will be helpful in the use of genetic resources in future breeding programs. In addition, our study demonstrates that SSR markers are highly suitable for further genetic diversity analyses of Chinese wild grapes.
... VVS2 (Thomas and Scott, 1993); VVMD5, VVMD7, VVMD25, VVMD27, VVMD28, VVMD32 (Bowers et al., 1999), VrZAG-62 and VrZAG-79 (Sefc et al., 1999). The protocol used was as described by Žulj Mihaljević et al. (2013). Genetic profiles were compared with varieties from Dalmatia (Croatia) at the Faculty of Agriculture and Food Technology (Zagreb). ...
... Six SSR markers loci were tested in this research using standard primers VVS2 (Thomas and Scott, 1993), VVMD5, VVMD7, VVMD27 (Bowers et al., 1999;Bowers et al., 1996), ssrZAG62 and ssrZAG79 (Sefc et al., 1999). All PCR amplifications were carried out in a Veriti thermal cycler (Applied Biosystems, Foster City, CA) using method described previously (Žulj Mihaljević et al., 2013). Amplified products were separated on ABI-3130 Genetic Analyzer (Applied Biosystems) with a GeneScan-500 LIZ size standard (Thermo Fisher Scientific). ...
... Hundreds of microsatellite markers for grapevines have been developed and most of them are publicly available ( Bowers et al. 1996;Arroyo-Garcia & Martinez-Zapater, 2004;Adam-Blondon et al. 2004;Merdinoglu et al. 2005;Cipriani et al. 2008). A set of six (VVS2, VVMD5, VVMD7, VVMD27, VrZag62, VrZAG79) or nine (previous six, combined with the following three: VVMD32, VVMD36, VVMD25) microsatellite markers has been used in grapevine genotyping studies, mostly for determining genetic variability among European grapevine cultivars, which are highly polymorphic (Sefc et al. 2001;This et al. 2004;Žulj et al. 2013). Aim of this research was extraction total DNA, primer selection and design, PCR protocols and analysis of DNA sequences with special emphasize on variability between collected samples of different grapevine cultivars. ...
Article
Full-text available
Indigenous grape varieties represent a significant potential for viticultural diversification. Due to fertilization problems, certain varieties from this group require suitable pollenizers for successful fertilization and in order to achieve high-quality grapes. The study was conducted during the years 2016 and 2017 in the vineyard in Herzegovina (southern part of Bosnia and Herzegovina). The aim of this research is to define a suitable pollenizer for the ‘Blatina’ variety, which has a functionally female flower. Manual pollination was performed with five different pollenizers during the flowering period by applying pollen to the ‘Blatina’ variety inflorescence during the full bloom stage in the early morning hours. Pollinated inflorescences were isolated, marked, and monitored until the end of the vegetation, while open-pollinated clusters were the control group. The most important characteristics of grape clusters and seeds were analyzed. The best results during the research were obtained by open pollination. The significant effect of the pollenizers was registered in parameters: cluster mass, mass of grape berries in the cluster, number of grape berries per cluster, and average seed mass. Varieties ‘Žilavka’ and ‘Vranac’ had better characteristics compared to other pollenizer varieties. The results show that the Blatina variety production with a greater number of pollenizers ensures stable yields.
Article
Full-text available
Thirty-one grape cultivars from France and Northwestern Italy, presumed to be synonymous, were analyzed using RAPD (Random Amplified Polymorphic DNA) and SSR (Simple Sequence Repeats or microsatellite) markers to verify 25 synonym hypotheses. RAPD analyses were performed with 8 selected decamer primers and the profiles of 7 microsatellite loci were used in order to confirm RAPD results, if required. Sixteen synonymies were confirmed, including the French cv. Verdesse with the Italian cv. Bian ver, the French cv. Persan with the Italian cv. Biquet, the French cv. Chatus with the Italian cv. Neiret, the French cv. Gouais blanc with the Italian cvs Preveiral and Liseiret. Most of the investigated cultivars belong to the Vitis vinifera germplasm of both sides of the Western Alps and the occurrence of synonyms indicates the existence of a common pool of grapes grown under different names in this part of Europe.
Article
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Aims: Eleven Macedonian grapevine accessions were genotyped by microsatellite profiling at 9 microsatellite loci, in order to identify Macedonian cultivars and to evaluate the relationships among them. The comparison with grapevine cultivars from two neighbouring countries was also performed. Methods and results: Clustering analyses based on the proportion of shared alleles resulted in two clusters containing all accessions except cultivar « Vranec », which was distant from the others. Comparison of genotyping results of Macedonian accessions with 76 Bulgarian and 298 Greek accessions revealed no identical genotypes. In the dendogram, Macedonian accessions are dispersed among Greek and Bulgarian grapevines, suggesting a common genetic background. Additionaly, the synonyms « Smederevka » = « Dimyat » = « Zoumiatiko » and « Belo Zimsko » = « Karatsova Naousis » were also evaluated. Conclusions: Clustering analyses showed that authentic Macedonian cultivars are distant from two widespread cultivars « Vranec » and « Smederevka ». Comparison of Macedonian cultivars with their synonyms from Greece and Bulgaria revealed differences in allelic profiles at some loci, but further analyses are needed to confirm their unique allelic profiles. Significance and impact of study: This work is a first step towards the genetic characterization of Macedonian grapevine germplasm, thus contributing to the molecular investigation of grapevine germplasm within the Balkan region.
Article
Full-text available
In order to identify grape varieties from Lig-uria (north-western Italy), 51 accessions (major, minor and neglected cultivars) were compared to those present in the grape collections of the neighbouring regions. Synonyms were confirmed by SSR markers (9 loci). Only 36 unique genetic profiles were found within grapes from Liguria, demonstrating the occurrence of synonyms with cultivars either from the same region or from other grape growing areas. Six evident misnames were found as well as homonyms. Four unexpected synonyms provided an opportunity to trace the likely origin and/or the movement of ancient cultivars, including 'Vernaccia di San Gimignano'.
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Four hundred twenty-one cultivated (Vitis vinifera ssp. sativa) and four alleged wild grapevine samples (putative Vitis vinifera ssp. sylvestris) from the Castilian Plateau in northern central Spain were genotyped at the six nuclear microsatellite loci (SSRs) proposed as a standard set for cultivar identification by the GENRES 081 project, yielding 121 different genotypes. The cultivated data set yielded 300 redundant samples, 13 homonyms, and 27 previously unreported genotypes, almost one-fourth of the nonredundant genotypes. Nonredundant genotypes were examined at another 16 nuclear and three chloroplast additional microsatellite loci for further analyses. Three differentiated genetic clusters were detected among them, separating (1) Muscat-type accessions and interspecific Vitis hybrids, (2) accessions from France and the western Castilian Plateau, and (3) accessions from the central Castilian Plateau together with local table grapes. The close relatedness of accessions from the western plateau among each other and to French varieties supported introduction of the latter along the pilgrimage route to Santiago de Compostela. White-berried cultivars from the central plateau were also closely related. Chlorotype data suggested that previously unpublished genotypes and autochthonous Castilian varieties had local origins or resulted from crosses between introduced and local varieties. Morphological features and allelic composition suggested that three of the four samples collected from wild habitats were closely related and might represent genuine Vitis vinifera ssp. sylvestris individuals.
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