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Received: 18 November 2024
Revised: 10 January 2025
Accepted: 10 January 2025
Published: 13 January 2025
Citation: Mekapogu, M.; Lim, S.-H.;
Choi, Y.-J.; Lee, S.-Y.; Jung, J.-A.
Evaluation of Genetic Diversity and
Identification of Cultivars in
Spray-Type Chrysanthemum Based on
SSR Markers. Genes 2025,16, 81.
https://doi.org/10.3390/
genes16010081
Copyright: © 2025 by the authors.
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This article is an open access article
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Article
Evaluation of Genetic Diversity and Identification of Cultivars in
Spray-Type Chrysanthemum Based on SSR Markers
Manjulatha Mekapogu , So-Hyeon Lim, Youn-Jung Choi, Su-Young Lee and Jae-A Jung *
Floriculture Research Division, National Institute of Horticultural & Herbal Science, Rural Development
Administration, Wanju 55365, Republic of Korea
*Correspondence: jabisung@korea.kr
Abstract: Background/Objectives: Chrysanthemum (Chrysanthemum morifolium), a key
ornamental and medicinal plant, presents challenges in cultivar identification due to high
phenotypic similarity and environmental influences. This study assessed the genetic di-
versity and discrimination of 126 spray-type chrysanthemum cultivars. Methods: About
twenty-three simple sequence repeat (SSR) markers were screened for the discrimination
of 126 cultivars, among which six SSR markers showed polymorphic fragments. Results:
Results showed high polymorphism across six markers, with an average of 3.8 alleles
per locus and a mean polymorphism information content (PIC) of 0.52, indicating strong
discriminatory efficiency. The average observed heterozygosity (Ho) was 0.72, reflecting
significant genetic diversity within the cultivars. Cluster analysis using the unweighted
pair group method with arithmetic mean (UPGMA) grouped the cultivars into seven
clusters, correlating well with the PCA. Bayesian population structure analysis suggested
two primary genetic subpopulations. Conclusions: These findings confirm SSR markers
as an effective tool for the genetic characterization and precise discrimination of spray
type chrysanthemum cultivars, offering significant applications in breeding, cultivar reg-
istration, and germplasm conservation. The SSR marker-based approach thus provides a
reliable and efficient strategy to enhance the management and commercialization of diverse
chrysanthemum germplasm collections.
Keywords: chrysanthemum; cultivar identification; genetic diversity; molecular markers;
ornamental plants; polymorphism; simple sequence repeat (SSR) markers
1. Introduction
Chrysanthemum (C.morifolium), belonging to the Asteraceae family, is a perennial
flowering plant and a commercially influential ornamental crop. It is one of the top
four most popular cut flowers after the rose, accounting for more than 30% of global
cut flower production and making a substantial contribution to the international floral
market. Chrysanthemum species also have medicinal and cosmetic value due to their
antipyretic, antioxidant, and anti-inflammatory properties [
1
]. In addition to cut flowers,
chrysanthemums are extensively used as potted ornamental plants, garden cover, and
in landscaping [
2
]. The rich diversity in chrysanthemum’s floral colors, shapes, and
sizes offers high aesthetic appeal and substantial economic significance. Ploidy levels in
chrysanthemum species range from diploid to decaploid, with cultivated chrysanthemum
exhibiting hexaploidy, comprising a stable configuration of 2n = 6x = 54 [3]. This complex
genome and allohexaploid nature are the primary reasons for the exceptional diversity in
both floral and architectural phenotypes [4].
Genes 2025,16, 81 https://doi.org/10.3390/genes16010081
Genes 2025,16, 81 2 of 14
The propagation of chrysanthemums by vegetative cuttings and plenty of inherent
genetic variation allows easier genetic manipulations, resulting in diverse phenotypic vari-
ations [
5
]. This genome complexity allows for substantial possibilities for morphological
variation even among closely related genotypes, leading to the commercialization of many
cultivars annually, contributing to the multi-billion-dollar floral industry. Although hun-
dreds of cultivars are available, the annual rise in global demand for chrysanthemum cut
flowers drives breeders to develop novel cultivars. However, most cultivars share similar
flower phenotypes, posing challenges for morphological differentiation [
6
]. Widely used
traditional morphological identification methods are often limited by environmental influ-
ences and high morphological similarity among cultivars, leading to poor identification
and classification on the market [
7
]. Additionally, the multigenic nature of morphological
features and their dependency on specific growth phases, influenced by environmental con-
ditions, hinder accurate cultivar characterization [
8
]. The identification and discrimination
of varieties are vital for breeding, seed production, selection, registration, market trade,
and inspection [
9
]. The identical floral phenotype among many commercialized cultivars,
along with numerous synonyms for local varieties, results in incorrect labeling, posing
significant challenges in cultivar assignment. Therefore, an efficient method is essential for
accurate variety discrimination, precise market labeling, and securing breeders’ intellectual
property rights.
Since phenotypic approaches are imprecise, labor-intensive, and less informative,
molecular markers offer a rapid and cost-effective alternative for variety identification [
10
].
DNA fingerprinting methods provide promising applications for breeders and growers in
cultivar identification, helping to avoid the problems of propagating or selling cultivars
without permission or incorrect labels. Molecular marker-based identification is rapid
compared to traditional approaches, which require growing questionable plants until the
flowering stage [
11
]. Although traditional methods continue to be used for distinctive-
ness, uniformity, and stability (DUS) testing in the registration of new cultivars and for
granting breeders intellectual property rights (IPR), these methods are less effective when
rapid results are required and when large numbers of cultivars need to be distinguished.
For decades, molecular methods and DNA fingerprinting have been widely applied for
genotype and cultivar identification across various crops, enabling gene patenting, vari-
ety registration, and the detection of biopiracy and infringement of breeders’ intellectual
property rights [12].
Molecular marker-based methods are recommended for the DUS testing of varieties
with limited genetic diversity and are widely endorsed for the identification, certifica-
tion, and protection of new cultivars by the International Union for the Protection of New
Varieties of Plants (UPOV 2010) [
13
,
14
]. A wide variety of molecular markers have been pre-
viously applied in genetic studies of cultivated chrysanthemums [
15
–
18
]. Simple Sequence
Repeat (SSR) markers have the advantages of co-dominance, abundance, their multi-allelic
nature, high precision, and ease of scoring compared to other dominant markers, which
are more difficult to reproduce [
19
]. SSRs are highly polymorphic genetic markers used
in cultivar identification, pedigree reconstruction, and genetic mapping [
20
]. Like other
crops, large numbers of new chrysanthemum cultivars are commercialized annually to
meet global demand. Chrysanthemums are categorized as standard or spray type, with
standard types exhibiting a single large bloom per stem, while spray types have multiple
smaller blooms per stem [
21
,
22
]. Spray-type chrysanthemums, with a higher number of
flowers displaying a diverse range of colors, shapes, and sizes, are highly desirable in the
cut flower market. Several studies have successfully employed SSR markers for genetic
diversity analysis and the identification of cultivars across various chrysanthemum types,
including both spray and standard varieties [23–28].
Genes 2025,16, 81 3 of 14
Hence, this study aims to assess the effectiveness and informative capacity of SSR
markers to characterize spray-type chrysanthemum cultivars. We examined the genetic
characteristics of a diverse collection of these cultivars, evaluating the informativeness and
utility of SSR markers for assessing genetic diversity.
2. Materials and Methods
2.1. Plant Material
A total of 126 spray chrysanthemum cultivars, including both Korean and foreign
varieties, were used in this study. Rooting was induced from the plant cuttings of chrysan-
themum cultivars and the plantlets with roots were raised in the pots filled with a soil and
peat moss mixture and maintained in the natural greenhouse conditions. One-month-old
plantlets were then transplanted to the artificial soil bed with a 15
×
15 cm density. The
soil bed constituted perlite and peat moss in a 1:1 ratio. A randomized complete block
design was employed in each line with five replications for each cultivar in two separate
beds. Irrigation, fertilization, and other horticultural practices were followed through the
cultivation period. The daily photoperiod was 14 h to 16 h long, with a light intensity of
100
µ
mol photons m
−2
s
−1
. A temperature and relative humidity of 22
±
5
◦
C and 70–75%,
respectively, were maintained constantly in the green house. SSR analysis was performed
in ten plants from each cultivar.
2.2. Genomic DNA Extraction
Fully expanded, young, and healthy leaves from each cultivar were collected, frozen in
liquid nitrogen, and stored. Genomic DNA was extracted from the leaves using a DNeasy
plant mini kit (Qiagen, Hilden, Germany). DNA quantity and quality were checked using
the Quick Drop (Molecular Devices, San Jose, CA, USA). The samples were standardized
to 25 ng µL−1by diluting the DNA and used for SSR analysis.
2.3. SSR Amplification and Evaluation Using ABI Genetic Analyzer
The differentiation of the 126 chrysanthemum cultivars employed 23 SSR markers.
Highly polymorphic primer pairs were obtained from the previous studies and after the
primary screening of the twenty-three markers, six polymorphic SSR markers were selected
to be used for the characterization of the selected cultivars in this study [
25
,
26
]. Details
of the primers are presented in Table 1. The M13 tailing method was then applied for the
labelling of PCR products [
29
]. The PCR amplification of each SSR marker was carried out
by amplifying 25 ng of DNA in an independent reaction of 25
µ
L PCR reaction volume
comprising 8 pmol (5
′
FAM labelled) of primer pairs, 0.4 mM of dNTPs, and 0.3U of Taq
DNA polymerase combined with 1X Taq buffer, making up the total volume to 25
µ
L
with sterile water. The PCR reaction was executed in the thermocycler (Veriti, Applied
Biosystems, Waltham, MA, USA). Following the initial denaturation at 94
◦
C for 5 min,
35 cycles of denaturation at 94
◦
C for 60 s, annealing at 58
◦
C for 30 s, and extension at 72
◦
C for 45 s were employed and ended with a 30 min final extension at 72
◦
C. The resulting
PCR product (2
µ
L) was separated on 2.5% agarose gel. Clear and scorable amplification
patterns were visualized by DNA Loading STAR (Dyne Bio, Seongnam, South Korea). The
PCR reaction was repeated thrice to confirm its reproducibility. Further genetic analysis
was performed by mixing each of the PCR products (1
µ
L) with Hi-Di formamide (10
µ
L)
and GeneScan-500 ROX internal size standard (0.12
µ
L) per well. This mixture was further
analyzed on an ABI PRISM 3100XL Genetic Analyzer (Applied Biosystems, Waltham, MA,
USA). The resulting PCR fragment sizes, representing the corresponding SSR loci, were
read using GeneMapper (version3.7) software. The data derived from the ABI genetic
Genes 2025,16, 81 4 of 14
analyzer was further used for the genetic diversity analysis of the 126 chrysanthemum
cultivars.
Table 1. Details of the SSR primer pairs that were used to characterize 126 spray-type chrysanthemum
cultivars.
No.
Marker Primer Sequence Repeat Motif
Forward Reverse
1 SSR_48 TGAGATCATTCCCAACCTCC CTAGCGTCCAAAGAATTGGC (CCA)5
2 SSR_51 CCCCCTCTTCTTCTTCAACC CAATAGAAAGCGCGTGACAA (CCAA)4
3 SSR_52 AGTGACCCGAGCCAGATAGA CCGACAAATCATTTCCGTCT (ATA)5
4 SSR_127 TAACAAGGGGTTTCAGCGTC TCAGGAAGAACAACCCAACC (GGT)5
5 SSR_200 CCCAGAGAAGCGTGAGATTT TCCCCTGCTACTACCACCAC (GGT)5
6 SSR_222 AGCTAAAACAAACAAGCGGC GCGTTAACTGTGTCGGTTGA (ATC)5
7 SSR_330 CTGTTGAGCAGTTCAGGCAC GTGTGATCGAGGCGATTTTT (CAA)5
8 SSR_332 ACACCGAATAGGACGGACAG TTTTCTGAAGTCCCGACCAC (TGG)5
9 SSR_380 ACCAAAGGCAGCTCACAGTT CCTCCCTCACTCATCTCTGC (TGA)5
10 SSR_649 TCTTCCTCACACGCAAACAC AGCTGCCACTCGCTATCACT (ACC)7
11 SSR_706 CGATCACCATTCTTTTCCCA CCGATAAGTTCGTCCTTGGT (AG)8
12 SSR_728 TGGTTATGGGTGACCCTGAT AAGAAAGTGCAGGCCAAGAA (ATG)5
13 SSR_792 AGGAAGAAGATCGACACCCA AAGTTCGGGTTTCCCCATAC (TGA)6
14 SSR_863 CACAACCAGACAAGCCTTCA ACTAACGGCGGTAGCTGAGA (TC)6
15 SSR_4 ACAGTACACACACAGCCAACAC GTAATGCTTCCGTCTGCATAGC (CAA)4
16 SSR_7 AGGCCCAACTTTATTCACCC CCAAATCCAATCTCCGGC (GAG)4
17 SSR_9 CATTCACACTCACCTACACACC CCTCCCTCTCTTACAATGTCAC (TCA)4
18 SSR_16 ACAAGTAGTAGGAGGAGGAGGA CAGTGTAGCCGGTACAGAAGA (AGT)5
19 SSR_31 GGAAGCAAGTGTGTGGTTTC ACCTCCCCATAGAATCTTGAGC (TG)9
20 SSR_40 GACGGATTTTGAGCTTGGAG GAACCAATAATCCCGACACC (TA)13
21 SSR_42 CAAAGTACTACCAAACGCGG GTAACATTGAGGGTGTAGCAGC (CA)6
22 SSR_45 AAACAGCCTGACCCAATCTC GTCATCATCCAACCACCAAC (ATT)6
23 SSR_50 GATGGTGAGACATTGCGTCT GCTCAAGGATTATGGACACTGG (TTAT)4
2.4. Data Analysis
Microsatellite allele parameters, such as genetic diversity metrics, heterozygosity, allele
counts, allele frequency, and polymorphism information content (PIC), were analyzed using
PowerMarker v3.25 software [
30
]. The amplified SSR fragments analyzed were scored
as 1 for presence and 0 for absence. Genetic similarity clustering was performed using
the unweighted pair group method of arithmetic averages (UPGMA), and a dendrogram
was created using PAST v3.26 software with a bootstrap frequency of n = 100. Principal
Component Analysis (PCA) was also conducted using PAST v3.26.
To identify clusters of genetically similar individuals, a population structure analysis
was conducted using the Bayesian clustering approach in STRUCTURE v4.3.2 software
(Stanford University, Stanford, CA, USA) [
31
,
32
]. This clustering method accounts for
admixtures and correlated allele frequencies, providing insights into the origins and genetic
admixtures of the cultivars. Genotypes were classified into subpopulations based on maxi-
mum membership probability [
33
]. Parameters were set with a burn-in period of 50,000
followed by 100,000 Markov Chain Monte Carlo simulations. Optimal subpopulation num-
bers (K values) were evaluated from 1 to 10 using an admixture model. Likelihood variation
for each K value was assessed through ten independent runs, with the optimal K deter-
mined by LnP(K) and the second-order rate of change of likelihood (
∆
K) [
31
]. STRUCTURE
Selector, a web-based tool, was used for calculations and graph construction [32].
Genes 2025,16, 81 5 of 14
3. Results
3.1. Assessing Genetic Variation of SSR Markers
A total of 126 spray chrysanthemum cultivars, with diverse genetic backgrounds and
exhibiting wide range of floral colors and floral types, were evaluated by applying SSR
markers. A list of the tested cultivars, categorized by color and type, is shown in Table 2.
Among these 126 cultivars, the majority had yellow flowers (37), followed by pink (29),
green (23), purple (19), red (12), and orange (6). This collection included various flower
types, such as single, double, semi-double, anemone, and pompon (Figure 1).
Table 2. List of the 126 tested cultivars in this study, categorized by their flower color and type.
Single Pompon Anemone Decorative
Yellow
Biarittz Yellow, Fly
Cather, Azma,
Viking Duck, Noa
Yellow, Lerbin,
Hwiparam, Linekar
Salmon, Bacardi
Cream, Celebrate,
Amisa, Tweety,
Marble Bronze,
Vesvio Yellow, Enci
Lemon, and Major
Cream.
Ping Pong Golden,
Yellow Candy, Sei
Piaget Yellow,
Restone, Yellow Cap,
Lollipop Yellow,
Yellow Pangpang,
and Ping Pong
Yellow.
Mona Lisa Sunny,
Radost Yellow, Puma
Yellow, Ilweol, Gold
Rich, Mona Lisa
Splendid, and
Garden Party.
Deliwind, Ibis Sunny,
Ibis Lime, Euro
Sunny, Dante Yellow,
Saffier Sunny,
Champane Golden,
and Zembla Brazil.
Pink
Leonardo, Kingfisher,
Amellie Pink, Glory
Pink, Pinky, Cherry
Blossom, Secret Pink,
Pink Pride, Bacardi
Pearl, Yes Song,
Tanga Pink, Biarittz
Pink, Dellia Pink,
and Plasir D’amour.
Bonbon, Cheeks,
Pink Bubble, Pink
Pangpang, Sweet
Carpet, Sei Piajet
Pink, and Sei Piajet
White.
Argus, Saba, Mona
Lisa Pink, and
Chopin Pink.
Plano Dark, Dianta,
Donna Pink, Crystal
Pink, Dante, Pink
Velvet, Prima Donna,
and Enci.
Green
Sei Frill Green, Field
Green, Buffy, Sei
Green Needle, and
Emma Green.
Froggy, Groovy,
Green Hop, Country,
Whitney Pangpang,
Kiwi, Green Candy,
Pure Green, Ping
Pong Green, Green
Pangpang, Green
Bird, and Siberia.
Radost and Green
Diamond.
Antasia Green Dark,
Antasia Dark Lime,
and Windmill Green.
Purple
Lemon Eye, Purple
Cone, Handsome,
Namba AC, and Fire
Pink.
Pepe, Lollipop, and
Lollipop Purple.
Mona Lisa Purple,
Chopin Purple,
Disco Club, Namba,
and Albertine.
Red
Black Marble, Red
Marble, Relence,
Chilly, Dosol,
Burning, Wembley,
and Tobee.
Quinty Red, Lexy
Red, and Sunny
Pangpang.
Princeiling
Orange
Amellie (O), Orange
Marble, and Vivid
Scarlet.
Orange Pangpang
and Golden
Pangpang.
Orange ND and
Orange Memory.
Genes 2025,16, 81 6 of 14
Genes 2025, 16, x FOR PEER REVIEW 6 of 15
Figure 1. Spray type chrysanthemum cultivars representing various floral types and colors used in
this study. (i) Yellow cultivars—Yellow Marble (Single (S)), Early Bird (Double (D)), Gold Rich
(Anemone (A)), and Golden Pangpang (Pompon (P)); (ii) Pink cultivars—Glory Pink (S), Donna
Pink (D), Pink Diamond (A), and Pink Bubble (P); (iii) Green Cultivars—Field Green (S), Windmill
Green (D), Green Diamond (A), and Green Pangpang (P); (iv) Purple Cultivars—SACHRY8617 (S),
Purple Cone (D), Disco Club (A), and Purple Pangpang (P); (v) Red cultivars—Red Marble (S), 10B1-
173 (D), Bradford (A), and Rexy Red (P); and (vi) Orange Cultivars—Light Up (S), Orange Pangpang
(D), Chopin Orange (A), and Orange Ball (P).
Initially, twenty-three markers from the chrysanthemum SSR database were
screened to identify the highly polymorphic SSR markers, resulting in the detection of ten
SSR markers. After the further screening of these ten markers, six pairs of microsatellite
primers were observed to be highly polymorphic and were analyzed to assess their poly-
morphic efficiency among the 126 cultivars. All six SSR markers showed polymorphism
across the chrysanthemum cultivars (Figure 2i). Representative results obtained for the
loci SSR_51 and SSR_16 through the ABI genetic analyzer in different samples has been
shown in Figure 2 (ii and iii). Genetic variation analysis showed that these six SSR markers
generated 840 scorable bands representing 25 different alleles. The amplicon sizes of
markers varied from 142 to 274 bp. The number of alleles per marker were either three
(SSR_51, SSR_40), four (SSR_42), or five (SSR_4, SSR16), with a mean of 3.8 alleles per
locus. The six SSR markers showed an average major allele frequency (M
AF
) of 0.48 per
locus, with observed heterozygosity (HO) ranging from 0.60 to 0.79, with a mean of 0.72
(Table 3). The selected 126 cultivars showed an average gene diversity of 0.58, ranging
from 0.39 to 0.70. Tested SSR markers exhibited Polymorphism Information Content (PIC)
Figure 1. Spray type chrysanthemum cultivars representing various floral types and colors used
in this study. (i) Yellow cultivars—Yellow Marble (Single (S)), Early Bird (Double (D)), Gold Rich
(Anemone (A)), and Golden Pangpang (Pompon (P)); (ii) Pink cultivars—Glory Pink (S), Donna Pink
(D), Pink Diamond (A), and Pink Bubble (P); (iii) Green Cultivars—Field Green (S), Windmill Green
(D), Green Diamond (A), and Green Pangpang (P); (iv) Purple Cultivars—SACHRY8617 (S), Purple
Cone (D), Disco Club (A), and Purple Pangpang (P); (v) Red cultivars—Red Marble (S), 10B1-173 (D),
Bradford (A), and Rexy Red (P); and (vi) Orange Cultivars—Light Up (S), Orange Pangpang (D),
Chopin Orange (A), and Orange Ball (P).
Initially, twenty-three markers from the chrysanthemum SSR database were screened
to identify the highly polymorphic SSR markers, resulting in the detection of ten SSR
markers. After the further screening of these ten markers, six pairs of microsatellite primers
were observed to be highly polymorphic and were analyzed to assess their polymorphic
efficiency among the 126 cultivars. All six SSR markers showed polymorphism across the
chrysanthemum cultivars (Figure 2i). Representative results obtained for the loci SSR_51
and SSR_16 through the ABI genetic analyzer in different samples has been shown in
Figure 2(ii and iii). Genetic variation analysis showed that these six SSR markers generated
840 scorable bands representing 25 different alleles. The amplicon sizes of markers varied
from 142 to 274 bp. The number of alleles per marker were either three (SSR_51, SSR_40),
four (SSR_42), or five (SSR_4, SSR16), with a mean of 3.8 alleles per locus. The six SSR
markers showed an average major allele frequency (M
AF
) of 0.48 per locus, with observed
heterozygosity (HO) ranging from 0.60 to 0.79, with a mean of 0.72 (Table 3). The selected
126 cultivars showed an average gene diversity of 0.58, ranging from 0.39 to 0.70. Tested
Genes 2025,16, 81 7 of 14
SSR markers exhibited Polymorphism Information Content (PIC) varying from a low of
0.30 in SSR_51 to a high of 0.63 in SSR_16, with a mean PIC of 0.52 (Table 3).
Genes 2025, 16, x FOR PEER REVIEW 7 of 15
varying from a low of 0.30 in SSR_51 to a high of 0.63 in SSR_16, with a mean PIC of 0.52
(Table 3).
Figure 2. Representative images of (i) PCR amplicons of six SSR markers tested and separated on
agarose gel; and (ii&iii) chromatograms of SSR_51 and SSR_16 in different samples by ABI genetic
analyzer 3100xl.
Table 3. Microsatellite allele metrics constituting allele number, gene diversity, M
AF
, H
O
, and poly-
morphism information content in 126 spray-type chrysanthemum cultivars based on SSR markers.
S.No Marker Repeat Motiff Allele Size (bp) No. of Alleles Gene Diversity
¶
M
AF
*
Ho
§
PIC
1 SSR_51 (CCAA)4 197-252 3 0.39 0.62 0.76 0.30
2 KChSSR_4 (CAA)4 248-274 5 0.70 0.38 0.79 0.65
3 KChSSR_7 (GAG)4 240-267 3 0.62 0.44 0.60 0.57
4 KChSSR_16 (AGT)5 185-194 5 0.68 0.40 0.77 0.63
5 KChSSR_40 (TA)13 146-152 3 0.58 0.48 0.66 0.49
6 KChSSR_42 (CA)6 142-170 4 0.53 0.55 0.75 0.46
3.83 0.58 0.48 0.72 0.52
¶
Major allele frequency (M
AF
); *
observed heterozygosity (H
O
); and
§
polymorphism information
content.
3.2. Genetic Relationship Assessment of the Chrysanthemum Genotypes
The genetic relationships among the 126 spray-type chrysanthemum cultivars were
evaluated by constructing a dendrogram based on the molecular profiles produced by the
six SSR markers. A UPGMA cluster analysis was performed based on the Euclidean ge-
netic distance values to construct a dendrogram. The Euclidean distance coefficient
ranged from 0.10 to 3.00 across all the SSR markers. The dendrogram grouped all 126 cul-
tivars into two major clusters, and at a distance of 2.75, cultivars were grouped into three
and four subgroups in Cluster 1 and Cluster 2, respectively (Figure 3).
Figure 2. Representative images of (i) PCR amplicons of six SSR markers tested and separated on
agarose gel; and (ii &iii) chromatograms of SSR_51 and SSR_16 in different samples by ABI genetic
analyzer 3100xl.
Table 3. Microsatellite allele metrics constituting allele number, gene diversity, M
AF
, H
O
, and poly-
morphism information content in 126 spray-type chrysanthemum cultivars based on SSR markers.
S.No. Marker Repeat
Motiff
Allele Size
(bp)
No. of
Alleles
Gene
Diversity
¶MAF * Ho §PIC
1 SSR_51 (CCAA)4 197-252 3 0.39 0.62 0.76 0.30
2
KChSSR_4
(CAA)4 248-274 5 0.70 0.38 0.79 0.65
3
KChSSR_7
(GAG)4 240-267 3 0.62 0.44 0.60 0.57
4
KChSSR_16
(AGT)5 185-194 5 0.68 0.40 0.77 0.63
5
KChSSR_40
(TA)13 146-152 3 0.58 0.48 0.66 0.49
6
KChSSR_42
(CA)6 142-170 4 0.53 0.55 0.75 0.46
3.83 0.58 0.48 0.72 0.52
¶Major allele frequency (MAF); * observed heterozygosity (HO); and §polymorphism information content.
3.2. Genetic Relationship Assessment of the Chrysanthemum Genotypes
The genetic relationships among the 126 spray-type chrysanthemum cultivars were
evaluated by constructing a dendrogram based on the molecular profiles produced by the
six SSR markers. A UPGMA cluster analysis was performed based on the Euclidean genetic
distance values to construct a dendrogram. The Euclidean distance coefficient ranged from
0.10 to 3.00 across all the SSR markers. The dendrogram grouped all 126 cultivars into
two major clusters, and at a distance of 2.75, cultivars were grouped into three and four
subgroups in Cluster 1 and Cluster 2, respectively (Figure 3).
Genes 2025,16, 81 8 of 14
Genes 2025, 16, x FOR PEER REVIEW 8 of 15
Figure 3. Dendrogram illustrating the classification of 126 spray chrysanthemum cultivars, estab-
lished based on a UPGMA analysis using SSR markers. Various clusters are shown on the right side
of the dendrogram. The scale at the top is the Euclidean distance.
The clustering analysis grouped the 126 chrysanthemum cultivars into two major
clusters with three and four sub-groups within each cluster. In Cluster 1, sub-group 1 con-
tained three green, pompon-type cultivars, while sub-group 2 included six cultivars com-
prising two spoon types and one each of pompon, semi-double, single, and anemone
types, with respective flower colors of yellow, red, pink, purple, and pink. Sub-group 3
included nine yellow cultivars (including four decorative, three single, and one each of
anemone and pompon types), three pink cultivars (two anemone and one decorative), one
purple (anemone), and one green (pompon). Sub-group 1 of Cluster 2 was a larger group
containing 27 cultivars: 11 pink (five single, four pompon, and two decorative), six yellow
(all single), three purple (two anemone, one single), three orange (two single, one semi-
double), two red (one single, one pompon), and two green (anemone). Sub-group 2 com-
prised 12 cultivars, including five green (two single, one each of anemone, decorative, and
pompon types), two single types in yellow and pink, and one pompon type each in purple,
orange, and red. The sub-group 3 was the largest and included 36 cultivars, primarily pink
(12), yellow (8), purple (5), red (5), green (3), and orange (3), spanning various floral forms.
Finally, Cluster 7 consisted of 28 cultivars, predominantly yellow (11), followed by green
(9), purple (2), and three each of purple and red cultivars.
Certain cultivar groups showed close genetic relationships within clusters. For in-
stance, two yellow decorative-type cultivars from the Ibis series, Ibis Sunny and Ibis Lime,
grouped closely in sub-group 3. Similarly, three anemone-type Mona Lisa cultivars with
pink, purple, and yellow flowers clustered together in sub-group 3. However, Mona Lisa
Figure 3. Dendrogram illustrating the classification of 126 spray chrysanthemum cultivars, estab-
lished based on a UPGMA analysis using SSR markers. Various clusters are shown on the right side
of the dendrogram. The scale at the top is the Euclidean distance.
The clustering analysis grouped the 126 chrysanthemum cultivars into two major
clusters with three and four sub-groups within each cluster. In Cluster 1, sub-group 1
contained three green, pompon-type cultivars, while sub-group 2 included six cultivars
comprising two spoon types and one each of pompon, semi-double, single, and anemone
types, with respective flower colors of yellow, red, pink, purple, and pink. Sub-group 3
included nine yellow cultivars (including four decorative, three single, and one each of
anemone and pompon types), three pink cultivars (two anemone and one decorative),
one purple (anemone), and one green (pompon). Sub-group 1 of Cluster 2 was a larger
group containing 27 cultivars: 11 pink (five single, four pompon, and two decorative), six
yellow (all single), three purple (two anemone, one single), three orange (two single, one
semi-double), two red (one single, one pompon), and two green (anemone). Sub-group 2
comprised 12 cultivars, including five green (two single, one each of anemone, decorative,
and pompon types), two single types in yellow and pink, and one pompon type each
in purple, orange, and red. The sub-group 3 was the largest and included 36 cultivars,
primarily pink (12), yellow (8), purple (5), red (5), green (3), and orange (3), spanning
various floral forms. Finally, Cluster 7 consisted of 28 cultivars, predominantly yellow (11),
followed by green (9), purple (2), and three each of purple and red cultivars.
Certain cultivar groups showed close genetic relationships within clusters. For in-
stance, two yellow decorative-type cultivars from the Ibis series, Ibis Sunny and Ibis Lime,
grouped closely in sub-group 3. Similarly, three anemone-type Mona Lisa cultivars with
pink, purple, and yellow flowers clustered together in sub-group 3. However, Mona Lisa
Genes 2025,16, 81 9 of 14
Splendid, another cultivar in this series with yellow anemone-type flowers, was positioned
distantly in sub-group 4, suggesting a different genetic background despite similar floral
characteristics. Other examples include pink and yellow pompon cultivars Sei Piaget Pink
and Sei Piaget Yellow, and the purple Namba and Namba AC cultivars with anemone and
single flower types grouped in sub-group 3 of Cluster 2. Purple pompon cultivars Lollipop
and Lollipop Purple showed a very close genetic relationship, indicating a shared genetic
background. The Principal Component Analysis (PCA) of the SSR data supported the
dendrogram findings, with cultivar groupings in the PCA plot aligning with the UPGMA
cluster analysis (Figure 4).
Genes 2025, 16, x FOR PEER REVIEW 9 of 15
Splendid, another cultivar in this series with yellow anemone-type flowers, was posi-
tioned distantly in sub-group 4, suggesting a different genetic background despite similar
floral characteristics. Other examples include pink and yellow pompon cultivars Sei Pia-
get Pink and Sei Piaget Yellow, and the purple Namba and Namba AC cultivars with
anemone and single flower types grouped in sub-group 3 of Cluster 2. Purple pompon
cultivars Lollipop and Lollipop Purple showed a very close genetic relationship, indicat-
ing a shared genetic background. The Principal Component Analysis (PCA) of the SSR
data supported the dendrogram findings, with cultivar groupings in the PCA plot align-
ing with the UPGMA cluster analysis (Figure 4).
Figure 4. Plot depicting the principle component analysis (PCA) of 126 chrysanthemum cultivars
based on SSR markers.
3.3. Population Structure Analysis
A population structure analysis was performed to assess genetic relationships and to
identify subpopulations among the cultivars. The number of genetically distant subpop-
ulations in the studied chrysanthemum cultivars were evaluated using the structure anal-
ysis. Individual cultivars were classified into relevant subpopulations based on the sys-
tematic analysis of the population structure using the Bayesian method in the Structure
software (v4.3.2). In this method of clustering, individual genotypes are allocated to K
clusters, where the Hardy–Weinberg law of equilibrium and linkage equilibrium are valid
within the clusters, while being absent between the clusters [34] . In our study, the ∆K
analysis revealed that the mean ∆K values were K = 2 among the 10 runs. Hence, K = 2
was the suitable value, suggesting that the studied population is subdivided into two sub-
populations (Figure 5). Figure 6 displays admixture plots for K = 2. At the ideal K = 2, all
of the 126 cultivars were categorized into two subpopulations. Group 1 comprised 59 cul-
tivars and Group 2 included 49 cultivars, whereas 17 cultivars shared a mixed population
ancestry.
Figure 4. Plot depicting the principle component analysis (PCA) of 126 chrysanthemum cultivars
based on SSR markers.
3.3. Population Structure Analysis
A population structure analysis was performed to assess genetic relationships and to
identify subpopulations among the cultivars. The number of genetically distant subpopula-
tions in the studied chrysanthemum cultivars were evaluated using the structure analysis.
Individual cultivars were classified into relevant subpopulations based on the systematic
analysis of the population structure using the Bayesian method in the Structure software
(v4.3.2). In this method of clustering, individual genotypes are allocated to K clusters,
where the Hardy–Weinberg law of equilibrium and linkage equilibrium are valid within
the clusters, while being absent between the clusters [
34
]. In our study, the
∆
K analysis
revealed that the mean
∆
K values were K = 2 among the 10 runs. Hence, K = 2 was the suit-
able value, suggesting that the studied population is subdivided into two subpopulations
(Figure 5). Figure 6displays admixture plots for K = 2. At the ideal K = 2, all of the 126
cultivars were categorized into two subpopulations. Group 1 comprised 59 cultivars and
Group 2 included 49 cultivars, whereas 17 cultivars shared a mixed population ancestry.
Genes 2025,16, 81 10 of 14
Genes 2025, 16, x FOR PEER REVIEW 10 of 15
Figure 5. Graphical illustration of the assessment of the best subpopulation numbers according to
the appropriate K value. (i) Mean of ∆K values representing 15 independent runs with K = 1 to K =
10 based on LnP(K) values. (ii) The mean of ∆K showed a peak at K = 2.
Figure 6. Genetic relatedness of individuals from 126 chrysanthemum cultivars, as analyzed by the
STRUCTURE software (v4.3.2). Y-axis values represent membership coefficients to subpopulations,
while X-axis values indicate the individual chrysanthemum cultivar codes of cultivars.
4. Discussion
The annual commercialization of numerous chrysanthemum cultivars, combined
with high morphological similarity, similar propagation methods, and shared genetic
backgrounds, presents significant challenges in distinguishing cultivars. Furthermore, lo-
cal nomenclature variations can complicate cultivar identification, which is essential for
breeding, cultivar registration, breeder’s intellectual property rights, market introduction,
and trade. Genetic characterization essential for the differentiation of germplasm can be
effectively determined by molecular markers [34,35]. As SSR markers are advantageous
over other markers in terms of high variability, co-dominance, cost-effective, precision
and reproducibility, they have been widely used for genetic characterization studies. SSR
markers have been used in constructing molecular maps and for intellectual property
rights evaluations [36]. Various earlier studies have highlighted their effectiveness in dis-
tinguishing chrysanthemum genotypes [23,37,38].
Previous studies established the SSR database that can be used for the assessment of
genetic relationships and the discrimination of cultivars in chrysanthemums [7,25,39]. For
Figure 5. Graphical illustration of the assessment of the best subpopulation numbers according to the
appropriate K value. (i) Mean of
∆
K values representing 15 independent runs with K = 1 to K = 10
based on LnP(K) values. (ii) The mean of ∆K showed a peak at K = 2.
Genes 2025, 16, x FOR PEER REVIEW 10 of 15
Figure 5. Graphical illustration of the assessment of the best subpopulation numbers according to
the appropriate K value. (i) Mean of ∆K values representing 15 independent runs with K = 1 to K =
10 based on LnP(K) values. (ii) The mean of ∆K showed a peak at K = 2.
Figure 6. Genetic relatedness of individuals from 126 chrysanthemum cultivars, as analyzed by the
STRUCTURE software (v4.3.2). Y-axis values represent membership coefficients to subpopulations,
while X-axis values indicate the individual chrysanthemum cultivar codes of cultivars.
4. Discussion
The annual commercialization of numerous chrysanthemum cultivars, combined
with high morphological similarity, similar propagation methods, and shared genetic
backgrounds, presents significant challenges in distinguishing cultivars. Furthermore, lo-
cal nomenclature variations can complicate cultivar identification, which is essential for
breeding, cultivar registration, breeder’s intellectual property rights, market introduction,
and trade. Genetic characterization essential for the differentiation of germplasm can be
effectively determined by molecular markers [34,35]. As SSR markers are advantageous
over other markers in terms of high variability, co-dominance, cost-effective, precision
and reproducibility, they have been widely used for genetic characterization studies. SSR
markers have been used in constructing molecular maps and for intellectual property
rights evaluations [36]. Various earlier studies have highlighted their effectiveness in dis-
tinguishing chrysanthemum genotypes [23,37,38].
Previous studies established the SSR database that can be used for the assessment of
genetic relationships and the discrimination of cultivars in chrysanthemums [7,25,39]. For
Figure 6. Genetic relatedness of individuals from 126 chrysanthemum cultivars, as analyzed by the
STRUCTURE software (v4.3.2). Y-axis values represent membership coefficients to subpopulations,
while X-axis values indicate the individual chrysanthemum cultivar codes of cultivars.
4. Discussion
The annual commercialization of numerous chrysanthemum cultivars, combined
with high morphological similarity, similar propagation methods, and shared genetic
backgrounds, presents significant challenges in distinguishing cultivars. Furthermore,
local nomenclature variations can complicate cultivar identification, which is essential for
breeding, cultivar registration, breeder’s intellectual property rights, market introduction,
and trade. Genetic characterization essential for the differentiation of germplasm can be
effectively determined by molecular markers [
34
,
35
]. As SSR markers are advantageous
over other markers in terms of high variability, co-dominance, cost-effective, precision
and reproducibility, they have been widely used for genetic characterization studies. SSR
markers have been used in constructing molecular maps and for intellectual property
rights evaluations [
36
]. Various earlier studies have highlighted their effectiveness in
distinguishing chrysanthemum genotypes [23,37,38].
Previous studies established the SSR database that can be used for the assessment of
genetic relationships and the discrimination of cultivars in chrysanthemums [
7
,
25
,
39
]. For
example, Shim et al. and Olejnik et al., in separate studies, used about 14 SSRs each to assess
the genetic relationship among 147 and 97 chrysanthemum cultivars, respectively [
7
,
25
].
Genes 2025,16, 81 11 of 14
Recent studies have employed SSR markers exclusively for standard-type chrysanthemums,
using different sets of SSRs to distinguish between cultivars [
26
,
27
,
40
,
41
]. In these studies,
eight, twenty-six, six, and twelve SSR markers were successfully applied to differentiate
fifty-six, thirty-six, eleven, and seven standard-type cultivars, respectively [
26
,
27
,
40
,
41
]. Ad-
ditionally, a significant number of closely related white-colored chrysanthemum cultivars
have been evaluated and genetically characterized using SSR marker sets [28].
In this study, we employed twenty-three SSR markers and, after the thorough screening
of these markers, six SSRs were used to assess the genetic diversity of 126 chrysanthemum
genotypes, representing various floral types and colors. Microsatellite parameters repre-
senting genetic diversity indicated the polymorphic nature of the six tested SSR markers
(Table 3). The number of alleles produced by SSRs ranged from three to five per locus,
with an average of 3.8 alleles per locus, which is similar to or higher than the previous
reports of SSR markers in chrysanthemums, with an average of 5.6, 3.5, and 3.7 alleles per
locus [
26
,
28
,
41
]. Variations in the number of alleles per locus can be affected by a number of
factors including geographical origin, number of genotypes tested, and the different types
of loci [
42
]. Observed heterozygosity (Ho) represents the genetic variability within the
genotypes [
43
]. The average Ho in this study for six markers was 0.72, indicating a higher
genetic variability in the 126 cultivars. This is comparable with findings from other chrysan-
themum studies reporting Ho average of 0.88, 0.89 0.67, 0.81, and 0.75 [
23
,
28
,
41
,
44
,
45
].
Based on these results, the average Ho can vary depending on the number of markers used.
The PIC, representing the degree of microsatellite polymorphism for the six SSR markers in
the evaluated 126 cultivars, ranged from 0.30 to 0.65, with an average of 0.52, indicating a
high degree of polymorphism in the SSR markers, as described by Botstein et al. [
46
]. In
separate studies, Khaing et al. [
44
], Jo et al. [
24
], and Chang et al. [
38
] observed a higher
PIC of 0.88 and a study by Kobeissi et al. [
47
] showed a PIC of 0.79. Slightly lower PICs of
0.50 and 0.53 were observed for 95 and 57 chrysanthemum cultivars, whereas a higher PIC
of 0.9 was recorded for 32 chrysanthemum cultivars [
18
,
28
,
48
]. Thus, PIC demonstrates the
discriminatory efficiency of SSR markers, inferring the genetic diversity of genotypes.
Genetic variations by SSR markers reveals the genetic relationship between the culti-
vars. In our study, tested SSR markers facilitated the genetic characterization of 126 cultivars
and the UPGMA dendrogram constructed based on the SSR data clustered the cultivars into
seven groups at a distance coefficient of 2.75 (Figure 3). Each cluster grouped genetically
similar cultivars, such as the three green pompon cultivars in sub-group 1 of Cluster 1.
Notably, two yellow decorative cultivars, Ibis Sunny and Ibis Lime, were closely related
within the same cluster, as were three differently colored cultivars from the Mona Lisa
anemone-type series (pink, purple, and yellow) in sub-group 3. In sub-group 1 of Cluster 2,
two pompon-type cultivars, Sei Piaget Pink and Sei Piaget Yellow, showed close genetic
similarity. Such genetic resemblance may result from the development of cultivar series
with different floral colors through mutation breeding, which is aimed at generating new
colors without altering other traits. For instance, Nagatomi et al. successfully produced
six mutant chrysanthemum varieties with diverse floral colors from a single parent [
49
].
Additionally, cultivar pairs such as Namba and Namba AC, as well as Lollipop and Lol-
lipop Purple in Cluster 6, exhibited near-identical genetic profiles, suggesting a shared
genetic background. Previous research has similarly observed high genetic similarity be-
tween standard and spray-type chrysanthemums [
26
–
28
]. The efficiency of SSR markers
for cultivar discrimination has been well demonstrated in recent studies. For example,
97 chrysanthemum cultivars were successfully distinguished based on different flower sizes
using 14 SSR markers, with small-flowered cultivars displaying higher genetic diversity [
7
].
Another study analyzed 36 chrysanthemum genotypes using 26 polymorphic SSR markers,
revealing high genetic diversity among the genotypes [
41
]. However, the lower resolution
Genes 2025,16, 81 12 of 14
level with a weaker branch support among the clusters is a limitation, which could be due
to the insufficient number of SSR markers used and hence, testing with a greater number of
SSR loci could efficiently differentiate the cultivars with a stronger resolution.
Population structure analysis in plants reflects various genetic factors, including
evolutionary history and gene flow within and between species [
35
]. In our study, the
population structure analysis indicated that the most suitable K value for the 126 cultivars
was two, grouping the cultivars into two genetic pools ( Figure 5; Figure 6). A mixed
population ancestry was observed across clusters, with cultivars like Namba, Secret Pink,
Fire Pink, Country, Lerbin, Biarrittz Pink, Noa Yellow, and Yellow Pangpang in Group 1
and Cheeks, Namba AC, Pink Pride, Hwiparam, Chilly, and Siberia in Group 2 showing
notable levels of admixture. This pattern aligns with previous chrysanthemum studies,
where population admixtures suggested genetic groupings of K = 2, K = 3, or K = 4 [
7
,
41
,
48
].
Mixed population structures in chrysanthemums are likely due to factors such as high
heterozygosity, self-incompatibility, and the breeding and domestication history of the
species [16,50].
5. Conclusions
In conclusion, this study provides a comprehensive genetic characterization of a di-
verse collection of 126 spray-type chrysanthemum cultivars, encompassing various floral
types and colors. The results highlight the effectiveness of SSR markers in elucidating the
genetic relationships among these cultivars, facilitating precise discrimination of individual
genotypes within the collection. The SSR marker-based approach proves to be a valuable
tool for distinguishing closely related genotypes and can be applied to the pedigree anal-
ysis, certification, and registration of chrysanthemum cultivars. Here, six SSR markers
were found to be efficient in characterizing the larger number of cultivars in this study.
However, the dendrogram differentiating the cultivars showed a weaker branch support,
which is a limitation of the lower number of SSR markers applied. Hence, employing
a greater number of markers in future studies would be more effective for the rigorous
genetic characterization of closely related cultivars. These findings therefore establish
a foundational platform for leveraging SSR markers in breeding programs, germplasm
conservation, and accelerating selection processes through the genetic characterization of
extensive genetic resource collections.
Author Contributions: Conceptualization, J.-A.J.; methodology, M.M.; investigation, M.M.; software,
M.M.; validation and formal analysis, M.M.; resources, S.-H.L., Y.-J.C. and S.-Y.L.; writing—original
draft preparation, M.M.; writing—review and editing, M.M. and J.-A.J.; funding acquisition, J.-A.J.
All authors have read and agreed to the published version of the manuscript.
Funding: This study was financially supported by the National Institute of Horticultural and Herbal
Science, Rural Development Administration, Republic of Korea under the project grant PJ01098202.
Data Availability Statement: All datasets generated and analyzed in the current study are available
from the corresponding author upon request.
Conflicts of Interest: The authors declare no conflicts of interest.
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