1. No category

BIHAREAN BIOLOGIST 9 (1): 47-54
Article No.: 141131
©Biharean Biologist, Oradea, Romania, 2015
http://biozoojournals.ro/bihbiol/index.html
Genetic diversity and phylogenetic relationship of Iranian indigenous cucurbits investigated
by Inter Simple Sequence Repeat (ISSR) markers
Ehsan ESMAILNIA, Mehdi AREFRAD*, Samira SHABANI, Mohammadreza KARIMI,
Fatemeh VAFADAR and Ali DEHESTANI
Genetics and Agricultural Biotechnology Institute of Tabarestan (GABIT) Sari, Mazandaran, Iran. P.O.Box: 578, Tel: +98 151 382575
*Corresponding author, M. Arefrad, E-mail: mehdiarefrad@yahoo.com
Received: 27. April 2014 / Accepted: 22. September 2014 / Available online: 11. April 2015 / Printed: June 2015
Abstract. Inter Simple Sequence Repeat (ISSR) markers were employed to study the genetic diversity among 30 indigenous species
of Iranian cucurbit from five different genera of Cucurbitaceae. Eleven out of seventeen studied primers amplified a total of 283
bands, out of which 263 (92.93%) were polymorphic. The mean Polymorphism Information Content (PIC) was estimated at 0.327.
Among the primers, ISSR15 exhibited the highest polymorphic bands and PIC value and was recognized as the most appropriate
and discriminating primer to investigate genetic diversity. The results of clustering analysis showed that the least distance was
observed between two species of Cucumis L. genus from Mashhad and Sabzevar with a genetic similarity value of 68.34%, while the
highest genetic distance was observed between two species of Cucumis L. and Cucurbita L. genera from Dastgerd and Hamadan with
a genetic similarity value of 20.71%. Although Cucurbita maxima and Cucurbita maschata were genetically similar, they weren't
classified in the same cluster. These results indicated an extensive genetic variation within Iranian Cucumis L. and Cucurbita L.
germplasm. The high genetic variability among studied species would be beneficial for selection of a core collection to facilitate
germplasm management to be used in cucurbit breeding and conservation programs. The results of the present study confirmed
that fingerprinting of cucurbits genotypes for identification purposes could be achieved by the ISSR technique.
Key words: Cucurbitaceae, intra and inter genus, genetic diversity, similarity matrix, ISSR markers.
Introduction
Cucurbits (Cucurbitaceae) are among the most important
plant families supplying humans with edible products and
useful fibers (Bisognin 2002). The main diversity center of
cucurbits was traditionally believed to be in Africa, however
recent molecular systematic studies, suggested that they
may be primarily originated from central and Southeast
Asia, West Africa, Madagascar and Mexico (Schaefer &
Renner 2011, Raghami et al. 2014). In addition, Sebastian et
al. (2010) proposed that melon and cucumber were both
originated from Asia and had numerous relatives in Australia and around the Indian Ocean which were overlooked
previously.
Several species of Cucurbitaceae are economically more
important than others including: melon (Cucumis melo L.);
cucumber (Cucumis sativus L.); watermelon (Citrullus lanatus); summer squash (Cucurbita pepo); winter squash (Cucurbita maschata); pumpkin (Cucurbita maxima); Bottlegourd (Lagenaria siceraria) and Loofah (Luffa acutangula) (Bisognin
2002). Although inter-specific hybridization of them have
been employed in breeding programs more than in any
other family, there is still a high potential for increasing its
application for germplasm and cultivar development (Bisognin 2002). Iran is one of the major cucurbit producers in
the world, as accounted for more than half of the total vegetable production and more than 150,000 ha area of agricultural land is devoted to cucurbit cultivation (second cucumber and gherkins producer) (FAO 2012). While there is no
improved cultivar of cucurbit family for growing commercially in Iran, and farmers have maintained local population
and exchanged seeds with surrounding areas (Barzegar et al.
2013). For an effective breeding program, information concerning the nature of genetic diversity within and among
species is a prerequisite for any crop improvement program.
Genetic diversity is commonly measured by genetic distance
or genetic similarity (Weir 1990). On the other hand, land-
races are important source of genetic diversity for improvement of cultivated species and they could be applied in
breeding programs.
Many studies have been employed to assess the genetic
diversity among the cucurbit family all over the world (Behera et al. 2008, Hadia et al. 2008, Dje et al. 2010, Ji et al. 2012,
Manohar et al. 2012, Zhang et al. 2012). In comparison to the
world, few studies have been conducted to illustrate the genetic variability and genetic phylogeny of the Iranian cucurbits. On the other hand, existing information is far from
drawing a precise picture of the genetic relationships in this
family. Some recent investigations through molecular methods have distinguished some unknown genotypes. In this
way Feyzian et al. (2007) assessed 38 Iranian melon accessions using RAPD markers, however these markers were not
able to discriminate horticultural groups of melon. Soltani et
al. (2010) showed a large variability in the Iranian melon
germplasm using RAPD, but they focused mainly on Cucumis melo var. flexuosus. Raghami et al. (2014) studied 24 Iranian melon accessions along with 28 other melon genotypes
from other countries using SSR markers and reported a low
genetic variability for Iranian melon germplasm.
Many methods have been employed to assess the genetic
diversity among the cucurbit family, ranging from morphological traits to molecular markers. Recently, most of the
studies have been designed for assessment of genetic variation using molecular markers because they show genetic differences on a more detailed level without interferences from
environmental factors and they can be highly polymorphic
(e.g. Levi et al. 2004, Behera et al. 2008, Yi et al. 2009, Kong et
al. 2011). Various types of DNA markers such as RFLPs
(Garcia-Mas et al. 2000), AFLPs (Ferriol et al. 2003), SSRs
(Barzegar et al. 2013, Raghami et al. 2014), RAPD (Oshingboye et al. 2013) and ISSR (Dje et al. 2010) have been used to
determine genetic diversity in different species of Cucurbitaceae. Inter-simple sequence repeats (ISSRs) had been developed based on the microsatellite loci and the similar princi-
E. Esmailnia et al.
48
ple of RAPD. This molecular marker was reported to detect a
higher portion of genomic variation than RFLP and was considered to achieve a higher reproducibility than RAPD
markers (Zietkiewicz et al. 1994, Dalamu et al. 2012). Also
ISSR marker technology is repeatable, effective, simple and
quick, which combines together the advantages of RAPD,
SSR and AFLP resulting in lower cost as well as required
DNA amounts (Reddy et al. 2002, Hadia et al. 2008, Wang et
al. 2009, Dje et al. 2010). In addition, ISSR markers have a
greater robustness in repeatability and show a high variability (Bornet & Branchard 2001). It seems that ISSR molecular
markers are more useful because they show high genetic
polymorphism, providing valuable site information and revealing the various microsatellite variations between individuals (Reddy et al. 2002).
A correct understanding of the genetic relationship and
genetic variability of the plant populations is an essential
prerequisite for any successful breeding program. In order to
complete the information of Iranian cucurbit germplasm and
develop the production of improved cucurbits cultivars this
investigation was designed. The objective of this study was
to identify inter-genus and intra-genus phylogenetic relationships, genetic diversity and distance among and within
some cultivated, commercial and wild species of Cucurbitaceae from different regions of Iran using ISSR molecular
marker.
DNA extraction
Approximately 100 mg of fresh young leaves of each accession was
grinded into powder with liquid nitrogen. Then the genomic DNA
was extracted through Dellaporta method (Dellaporta et al. 1983)
with some modifications. DNA pellet was dissolved in 50 μL of
ddH2O. Extracted DNA was quantified on 0.8% agarose gel, with a
run time of 60 min at 90 V in 1X TAE buffer, and the concentration
was evaluated by spectrophotometer. Finally, the DNA samples
were stored at - 20 °C for further studies.
Figure 1. Geographical distribution of the sampling area from which
the investigated genotypes were collected.
Materials and methods
Plant material
Thirty different species of Cucurbitaceae were investigated; twenty
six local species from five distinct genera (Cucumis L., Cucurbita L.,
Lagenaria L., Citrullus L. and Luffa L.), three commercial cultivars and
one wild species. Seeds of these species were collected from several
provinces of Iran including Tehran, Mazandaran, Golestan, Isfahan,
Gilan, Hamadan, Khuzestan, Azarbaijan, Khorasan-Razavi and
Semnan (Fig. 1). Among thirty species, twenty one species were belonged to Cucumis L. genus, six species related to Cucurbita L. genus
and one species from each of Luffa L., Lagenaria L. and Citrullus L.
genus (Table 1). The seeds of thirty species were planted in Genetics
and Agricultural Biotechnology Institute of Tabarestan (GABIT) research farm and the young, newly developed leaves were collected
for subsequent DNA extraction.
Polymerase Chain Reaction (PCR) and gel electrophoresis
A preliminary screening was carried out; using seventeen inter simple sequence repeat (ISSR) primers in order to select those with polymorphic, reproducible bands. Standardized PCR reaction mixture
consisted 12 μL of a solution containing 8.19 μL of water, 70 ng genomic DNA, 0.2 μL (1 unit per reaction) of Taq DNA polymerase,
0.32 μL dNTP mix, 0.94 μL primer in 1X PCR reaction buffer. Amplification condition were performed in a thermocycler (Applied Biosystems, Budapest, Hungary) which were programmed as follows:
an initial denaturation step at 94 °C for 5 min followed by 35 amplification cycles with three steps for each: 1 min denaturation at 94 °C,
1 min annealing at 53-56 °C, and 1 min elongation at 72 °C. The reactions were followed by a 7 min extension at 72 °C and were eventu-
Table 1. Names and origin of the 30 cucurbit genotypes studied using ISSR markers.
Code Name
Sampling region Code Name
1
Gorgab
16
Cucumis melo
Dezful
2
Cucumis melo var. reticulatus
Cucurbita maxima
Sanandaj
17
Cucumis melo
Garmsar
3
Cucumis melo
Dezful
18
Citrullus lanatus
Commercial
4
Gorgan
19
Cucurbita maschata
Babol
5
Cucumis melo
Cucumis melo
Sabzevar
20
6
Luffa acutangula
----------
21
7
Lagenaria siceraria
Babolsar
22
Cucumis melo var. cantalupensis Varamin
Cucumis sativus
Dastgerd
Cucumis melo
Commercial
8
Cucumis melo
Sabzevar
23
Cucurbita maschata
Shahrod
9
24
Cucumis melo
Sari
25
Cucurbita maschata
Babol
11
Cucumis melo var. cantalupensis Varamin
Cucumis sativus
Babol
Cucumis melo
Gorgan
26
Cucumis melo
Mashhad
12
Cucumis melo
Commercial
27
Rasht
13
Cucumis melo
Mashhad
28
Cucumis melo var. dudaim
Cucurbita maxima
14
Cucumis melo
Sabzevar
29
Cucumis melo
Dezful
15
Cucumis melo var. agrestis
Gorgan
30
Cucurbita maxima
Hamadan
10
Sampling region
Urmia
Genetic diversity of Iranian cucurbits
ally stored at 4 °C. The results of amplification reactions were analyzed on 1.8% agarose gel in 1X TAE buffer and run at 85 V for 2
hours. Thereafter, amplified fragments were stained with ethidium
bromide solution and visualized under UV radiation (Sambrook et
al. 2001).
Data analysis
After visualization and documentation of gels, data analyses were
performed. In the genetic relationship study, each amplified fragment was treated as a unit character regardless of its intensity and
scored in terms of a binary code (presence-1, absence-0) in each studied genotype, thus creating a binary data matrix. Since ISSR is a
dominant marker, the presence of a band was interpreted as either a
heterozygote or dominant homozygote and the absence of a band as
a recessive homozygote. The data matrix structure was assembled by
binomial (0/1) data and used as input data for further analysis using
NTSYS version 2.02 software program (Rohlf 1998). To test whether
clusters in the dendrogram agreed with information from the similarity matrix, cophenetic correlation matrices were created from the
dendrogram and compared with the similarity matrix. Similarity for
ISSR data was computed using the Jaccard’s similarity index and
cluster diagrams were generated with the Unweighted Pair Group
Method using Arithmetic averages (UPGMA) algorithm. The resulting clusters were expressed as dendrogram. Allelic polymorphism
Information Content (PIC) was calculated for each locus by the formula: PIC = 2Pi (1 - Pi) (Bhat 2002). Principal Component Analysis
(PCA), a multivariate approach which is more informative regarding
distances among major groups (Hauser & Crovello 1982), was performed. This can complement the cluster analysis and identify patterns of association among different accessions.
Results
Evaluation of ISSR PCR results
Characterization of the genetic relationship between cultivated, commercial, and wild species of some important genera of Cucurbitaceae was conducted by 17 ISSR primers, out
of which 11 primers exhibited clear and reproducible fragments with multiband patterns in each genotype that were
selected for further analysis and considered as informative
and polymorphic primers (Fig. 2). Amplification with the selected primers allowed the visualization of 283 bands with
sizes between 200 to 2500 bp, of which 263 bands were polymorphic (92.27%). The highest number of bands was produced by ISSR9 (total of 36 bands) and the lowest number of
bands was obtained by ISSR17 (18 bands), with an average
number of 25.72 bands per primer. The percentage of polymorphism ranged from 72% for ISSR20 to 100% for ISSR9,
ISSR11, ISSR15 and ISSR18, with an average of 92.27%
polymorphism per primer. The ISSR18 exhibited the highest
size variation of amplified fragments (200-2500 bp) and the
lowest size variation was observed for ISSR20 (200-800 bp).
The PIC value varied from 0.221 (ISSR20) to 0.391 (ISSR15),
with an average of 0.327. The highest and lowest PIC values
were obtained by ISSR15 and ISSR20, respectively. Characteristics of all primers have been shown in Table 2.
Genetic relationship and clustering analysis
Genetic similarity was varied from 20.71% to 68.34%, with
an average of 41.7%. The highest similarity was observed
among two species of Cucumis L. genus (C. melo L. from
Mashhad and Sabzevar) with a genetic similarity value of
68.34% (Table 3). Also it was revealed that the least similarity was observed between two species of Cucumis L. and Cu-
49
curbita L. genera (C. sativus L. from Dastgerd and C. maxima
from Hamadan, respectively) with a genetic similarity value
of 20.71%.
To construct a dendrogram, the cophenetic correlation
coefficient, a measure of the correlation between the similarity represented on the dendrogram and the actual degree of
similarity was calculated for each genotype. Among different methods, the highest value was observed for UPGMA
based on Jaccard’s coefficient (r = 0.876) corresponding to a
good fit. The dendrogram divided the investigated species
into seven major clusters (Fig. 3). The first main cluster with
a genetic similarity value of 40% divided into two subclusters in which all species of Cucumis melo L. were located.
The first sub-clusters with a genetic similarity value of 47%
comprises of six species of which four species related to C.
melo (G3, G4, G5 and G8 ) and two others related to two varieties of C. melo including var. reticulatus (G1) and var. cantalupensis (G9). The second sub-cluster with a genetic similarity value of 45.5% consists of thirteen species of C. melo
(G11, G12, G13, G14, G15, G20, G22, G29, G26, G24, G27, G16
and G17). The second main cluster formed by species of Cucumis sativus (G10 and G21) which has a genetic similarity
value of 42.9%. The third main cluster consisted of two subclusters with a genetic similarity value of 40.5%. In the first
sub-cluster the only species of Luffa L. genus (G6) located
and in the second one two species of Cucurbita maschata (G19
and G25) and one species of Cucurbita maxima (G28) placed.
Three species of Citrullus lanatus (G18), Lagenaria siceraria
(G7) and one species of Cucurbita maschata (G23) separately
made the fourth, fifth and sixth clusters respectively. Two
species of C. maxima (G2 and G30) made the seventh cluster
with a genetic similarity value of 30% (Fig. 3).
Principle Component Analysis (PCA) was performed
based on the similarity matrix to describe the variability and
relationship among accessions in a two-dimensional mode.
There was a high accordance between the results of PCA and
clustering dendrogram but accessions weren't separated
precisely by PCA when compared with UPGMA dendrogram (Fig. 4).
Discussion
The information on polymorphism is useful in the assessment of genetic diversity, genetic relationships and in the
breeding programs (Hadia et al. 2008). High level of polymorphism between investigated species of Cucurbitaceae
was separately obtained by Stepansky et al. (1999) in Cucumis melo L.; Levi et al. (2004) in Citrullus lanatus; Dey et al.
(2006) in bitter gourd; Hadia et al. (2008) in three species of
Cucurbita L. genus (C. pepo, C. maxima and C. moschata); Dje
et al. (2010) in C. lanatus and Manohar et al. (2012) in Cucumis sativus. In addition some other reports demonstrated that
RAPD markers showed lower polymorphism with (6.9
bands/alleles and 70% of polymorphic bands) than ISSR
with (9 bands/alleles and 90% of polymorphic bands)
among C. melo (Stepansky et al. 1999). Moreover, Paris et al.
(2003) and Sensoy et al. (2007) illustrated in Cucurbita pepo
and C. melo respectively that ISSR markers frequently detected a higher level of polymorphism than that detected
with other dominant markers (RAPD or AFLP). These re-
E. Esmailnia et al.
50
Figure 2. DNA fingerprinting patterns for 30 genotypes of Cucurbitaceae. ISSR profiles obtained
with primers A, ISSR12 and B, ISSR7. M, Molecular DNA marker.
Table 2. List of 11 ISSR primers, annealing temperatures, number of polymorphic band, percentage of polymorphic bands and Polymorphic Information Content (PIC = 2 pi (1 - pi)) generated by per primer used for
assessment of genetic diversity.
Primer
Sequence
(5' to 3')
Annealing
temperatures (°C)
Total no.
of band
No. of polymorphic
fragment
Polymorphism
(%)
PIC
0.337
ISSR 7
C(GA)8
54
29
26
90
ISSR 9
(AG)8C
55
36
36
100
0.352
ISSR 10
(AG)8G
55
32
30
94
0.353
0.363
ISSR 11
(GA)8C
55
26
26
100
ISSR 12
(GA)8A
54
26
23
89
0.304
ISSR 13
(TC)8C
54
19
18
95
0.350
0.391
ISSR 15
(AC)8G
55
20
20
100
ISSR 17
(AC)8C
54
18
15
83
0.246
ISSR 18
(ATC)6T
55
30
30
100
0.373
ISSR 19
(ATC)6C
56
26
24
92
0.309
ISSR 20
(ATG)6G
56
21
15
72
0.221
92.27
0.327
Total
283
263
Mean
25.72
23.91
sults confirmed that not only ISSR markers are extensive polymorphic within the studied species, but also they are especially efficient to distinguish the differences between genotypes and usefulness of them for genetic relationship analysis which can be useful in the breeding programs of cucurbit
family.
Polymorphic Information Content (PIC) is a parameter
that refers to the value of a marker for detecting the degree
of polymorphism within a population. To determine PIC
values of each ISSR primer we analyzed the mean of PIC
values for all loci of each ISSR primer. It is assumed that a
PIC > 0.5 accounts for a highly informative marker, 0.5 > PIC
> 0.25 for an informative marker, and PIC < 0.25 for a
slightly informative marker (Botstein et al. 1980). In the present study the polymorphic bands have PIC value between
0.25 and 0.5 which indicating that the ISSR markers used in
the present study were informative and they could be effectively used in genetic diversity studies and breeding programs. Behera et al. (2008) when defined the genetic diversity of bitter gourd, evaluated the PIC value of 0.17 and 0.40
for RAPD and ISSR respectively. Furthermore Inan et al.
(2012) illustrated the greater PIC values of 0.73 in some Cucurbita species by ISSR markers. The greater discriminatory
power of ISSR markers may be due to comparatively higher
values of average polymorphic information content as well
as the diverse nature of the genotypes.
The relative efficiency of molecular markers can be
measured by the amount of polymorphism and PIC value of
accessions under investigation (Grativol et al. 2011). Also,
Wang et al. (2009) stated that the relationship between genotypes depended on number and frequency of the amplified
fragments per primers. As a result, ISSR15 primer with the
highest polymorphic bands and PIC value was recognized as
the most appropriate and discriminating primer to estimate
genetic similarity among species of Cucurbitaceae.
Genetic similarity obtained in the present study, implying a high level of genetic variation between investigated
species (Table 3). These results is comparable with the results of Mohammed et al. (2012) who reported that the genetic similarity coefficients ranged between 0.15 and 0.62 in
10 cucurbits species using thirteen RAPD primers. Whereas,
Sidkar et al. (2010) reported lower genetic similarities ranged
from 9% to 30%, with a mean of 19% in eight genera of Cucurbitaceae by ISSR markers. The wide range of genetic
variation by ISSR markers in the present study revealed high
level of diversity among the Iranian germplasm of cucurbits
species.
All over the worlds (especially in Iranian) few studies
0.47
0.47
0.33
0.30
0.40
0.51
0.35
0.35
0.36
0.38
0.36
0.30
0.32
0.36
0.31
0.34
0.36
0.30
0.33
0.28
0.36
0.31
0.34
0.35
0.35
0.34
0.25
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
2
0.40
0.29
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0.30
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0.29
0.26
0.27
0.30
0.31
0.31
0.29
0.32
1.00
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0.39
0.33
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0.34
0.28
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0.32
0.32
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0.33
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0.31
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0.52
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3
0.30
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0.58
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1.00
5
0.34
0.36
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0.34
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0.32
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1.00
6
0.31
0.29
0.32
0.30
0.26
0.30
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0.30
0.35
0.32
0.36
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0.27
0.27
0.35
0.36
0.32
0.35
0.36
0.37
0.30
0.32
1.00
7
0.34
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0.38
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0.37
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8
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1.00
9
0.26
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1.00
10
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0.44
0.40
0.44
0.56
0.61
0.59
1.00
11
0.33
0.46
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0.43
0.42
0.29
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0.30
0.48
0.34
0.49
0.32
0.32
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0.48
0.64
0.66
1.00
12
0.35
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0.33
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0.35
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0.34
0.46
0.32
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0.32
0.46
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0.48
0.68
1.00
13
0.35
0.47
0.38
0.45
0.42
0.34
0.47
0.35
0.55
0.34
0.52
0.36
0.35
0.49
0.42
0.48
1.00
14
0.34
0.51
0.33
0.43
0.38
0.36
0.47
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0.46
0.35
0.46
0.33
0.31
0.39
0.35
1.00
15
0.31
0.37
0.27
0.38
0.35
0.26
0.33
0.23
0.40
0.31
0.40
0.25
0.36
0.58
1.00
16
0.26
0.45
0.35
0.44
0.42
0.29
0.40
0.28
0.46
0.37
0.49
0.31
0.39
1.00
17
0.32
0.34
0.26
0.31
0.32
0.30
0.34
0.27
0.33
0.34
0.28
0.30
1.00
18
0.39
0.35
0.46
0.31
0.34
0.57
0.35
0.36
0.36
0.25
0.30
1.00
19
0.30
0.54
0.38
0.46
0.49
0.32
0.53
0.33
0.63
0.38
1.00
20
0.21
0.39
0.32
0.35
0.35
0.32
0.35
0.29
0.45
1.00
21
0.32
0.64
0.39
0.52
0.50
0.38
0.54
0.34
1.00
22
0.29
0.33
0.30
0.29
0.33
0.34
0.33
1.00
23
0.38
0.54
0.38
0.48
0.46
0.36
1.00
24
0.32
0.37
0.52
0.35
0.33
1.00
25
0.32
0.63
0.38
0.49
1.00
26
0.34
0.59
0.37
1.00
27
0.29
0.42
1.00
28
0.32
1.00
29
1-Cucumis melo var. reticulatus, 2- Cucurbita maxima, 3- Cucumis melo, 4- Cucumis melo, 5- Cucumis melo, 6- Luffa acutangula, 7- Lagenaria siceraria, 8- Cucumis melo, 9- Cucumis melo var. cantalupensis, 10- Cucumis
sativus, 11- Cucumis melo, 12- Cucumis melo, 13- Cucumis melo, 14- Cucumis melo, 15- Cucumis melo var. agrestis, 16- Cucumis melo, 17- Cucumis melo, 18- Citrullus lanatus, 19- Cucurbita maschata, 20- Cucumis melo var.
cantalupensis, 21- Cucumis sativus, 22- Cucumis melo, 23- Cucurbita maschata, 24- Cucumis melo, 25- Cucurbita maschata, 26- Cucumis melo, 27- Cucumis melo var. dudaim, 28- Cucurbita maxima, 29- Cucumis melo,
30- Cucurbita maxima.
0.50
3
1
0.30
2
Table 3. Genetic similarity values among the 30 members of Iranian Cucurbitaceae genotypes as determined by 11 ISSR markers using Jaccard similarity coefficient.
E. Esmailnia et al.
52
Figure 3. Dendrogram based on Jaccard’s similarity coefficient and UPGMA algorithm showing the genetic relationship
among 30 genotypes of Cucurbitaceae family analyzed by ISSR markers.
Figure 4. 2D plot derived from Principal Component Analysis (PCA)
of 30 cucurbits accessions based on ISSR molecular markers.
have been conducted about genetic diversity at inter- and intra- genus level of Cucurbitaceae. Based on the genetic similarity value, UPGMA dendrogram and PCA diagram, the
highest similarity was observed among two species of Cucumis genus (C. melo from Mashhad and Sabzevar) with a
genetic similarity value of 68.34% (Table 3, Fig. 3 and 4). A
similar result was reported in Turkish melons (Sensoy et al.
2007) and cucumber (Hu et al. 2010). By contrast, after analyzing combined chloroplast sequences for 123 of the 130
genera of Cucurbitaceae, Renner et al. (2007) concluded that
genetic distance between Cucumis sativus and C. melo was
over estimated compared to their genetic distance based on
the morphological characteristics. Zhang et al. (2012) reported a high genetic similarity between C. sativus and C.
melo based on using molecular data and morphological
traits. Using SSR markers to study the Cucurbitaceae, Weng
(2010) demonstrated a high genetic similarity between melon
and cucumber (0.933). Interestingly, Kocyan et al. (2007) appraised phylogenetic relationships within Cucurbitaceae
based on chloroplast DNA sequences from two genes (Intron
and spacers) and indicated a high similarity between C. melo
and C. sativus. These results altogether strongly suggested
that different species of Cucumis genus are genetically similar, whereas different species of Cucumis and Cucurbita genera are genetically distant from each other.
Awareness the phylogenetic relationships in the genus
Cucumis are important, because the germplasm and natural
composition can provide valuable information to improve
melon and cucumber breeding (Zhang et al. 2012). According to the results all the Cucumis melo L. species sit in the first
cluster. Among them, two species from Mashhad and Sabzevar were the most closely related species with a similarity
value of 68.34% (Table 3). It was also observed that although
two species of Cucumis melo (G3 and G16) were collected
Genetic diversity of Iranian cucurbits
53
from same geographical origin (Dezful), they illustrated the Acknowledgements. This research was conducted with the financial
low similarity value of 29% (Table 3). These results are to support of the Genetics and Agricultural Biotechnology Institute of
some extent in agree with the Mohammed et al. (2012) who Tabarestan (GABIT), Sari, Iran.
reported that the most similarity was observed between two
species of C. melo with a genetic similarity of 62%. On the
other hand, In Japan Nakata et al. (2005) evaluated 67 melon
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