Research Article

Horticultural Science and Technology. 30 June 2020. 374-384
https://doi.org/10.7235/HORT.20200036

ABSTRACT


MAIN

  • Introduction

  • Materials and Methods

  •   Plant Materials and Genomic DNA Extraction

  •   Polymorphism Test of Microsatellite Marker Candidates

  •   Genotyping by M13-tailed PCR

  •   Data Analysis

  • Results and Discussion

  •   Development of Polymorphic Microsatellite Markers

  •   Identification of the Citrus Varieties Bred in Korea using Polymorphic Microsatellite Markers

Introduction

Citrus is a major fruit crop produced in tropical and subtropical regions around the world. Citrus annually produces 146 million tons of fruit from a cultivated area of 7.2 million hectares worldwide. Sweet orange cultivars account for approximately 60% of annual citrus production (FAO, 2018). In 2017, citrus produced over 0.6 million tons of fruit in the arable land of over 20,000 hectares in Korea. The entire production amounted to approximately 0.83 billion USD (www.krei.re.kr). Citrus fruit is an important source of nutrition for humans due to its high contents of vitamin C, citric acid, and other functional compounds, including citrus-specific flavonoids such as hesperidin and tangeretin (Benavente-García and Castillo, 2008; Iranshahi et al., 2015). Despite the tremendous extent and value of citrus production, most citrus varieties have been selected from natural hybridizations and somatic mutations (e.g., bud sport and nucellar mutants), not from systematic and targeted breeding programs (Talon and Gmitter, 2008). Citrus is considered the most difficult crop for developing new varieties through conventional breeding. Unfavorable factors for conventional breeding in citrus include large plant size, long juvenile stage, self- and cross-incompatibility, pollen and/or ovule sterility, high level of heterozygosity, and apomictic nucellar embryony (Donmez et al., 2013).

Microsatellites, also referred to as simple sequence repeats (SSRs), are highly informative DNA markers due to their high degree of polymorphism, codominant mode of inheritance, and genome-wide distribution (including organelle genomes). The International Union for the Protection of New Varieties of Plants (UPOV) highly recommends the use of molecular markers such as microsatellites to verify new varieties (UPOV, www.upov.int). Microsatellite markers have been widely used for various molecular genetic analyses, such as genetic diversity and population structure studies (Kim et al., 2016; Chung et al., 2019), construction of genetic linkage maps (Chang et al., 2018), identification of zygotic/ nucellar individuals (Woo et al., 2019), and cultivar/genotype identification (Kim et al., 2019).

In Korea, systematic citrus breeding programs have been in operation since the Citrus Research Institute, National Institute of Horticultural and Herbal Science, was established in 1992. More than 30 citrus varieties have been developed from bud sport mutants, nucellar mutants, and genetic hybridizations by breeders at governmental institutes and breeding companies as well as private breeders. Development of new citrus varieties will greatly increase in the near future due to citrus breeding programs in government and company sectors. However, reliable technologies for identifying Korean citrus varieties that protect breeders’ rights and guarantee the quality of nursery plants are not yet established. Therefore, in this study, we report the development of polymorphic microsatellite makers to identify citrus varieties bred in Korea.

Materials and Methods

Plant Materials and Genomic DNA Extraction

Leaf samples of citrus varieties used in this study were obtained from two public institutes in the Republic of Korea: Agricultural Research and Extension Services, Jeju Special Self-Governing Province, and Citrus Research Institute, National Institute of Horticultural & Herbal Science. Harvested leaf tissues were rinsed with running tap water and then stored at ‑ 80°C until use. Genomic DNA (gDNA) was isolated from the leaf tissue using the Biomedic® Plant gDNA Extraction Kit (Biomedic Co., Ltd., Bucheon, Korea). The isolated gDNA was quantified using the DeNovix DS-11+ spectrophotometer (DeNovix, Wilmington, DE, USA).

Polymorphism Test of Microsatellite Marker Candidates

Putative polymorphic microsatellite markers were selected from routine PCR using gDNAs from 11 varieties belonging to six citrus groups (lemon, mandarin, sour orange, citron, orange, and tangor) as described previously (Woo et al., 2019). The PCR reaction and cycling conditions were described in our previous report (Woo et al., 2019). PCR products were separated on a 2.5% (w/v) agarose gel to confirm PCR amplification and polymorphism among the tested varieties.

Genotyping by M13-tailed PCR

The M13-tailed PCR method was used for genotype analysis using the selected polymorphic microsatellite markers (Schuelke, 2000). The PCR reaction conditions were the same as those previously reported (Woo et al., 2019). The cycling conditions for PCR amplification followed the protocol described previously by Schuelke (2000). Fragment analysis of the PCR products was described previously (Kim et al., 2012). Calling of allele sizes was performed using GeneMapper software (ver. 4.0; Applied Biosystems).

Data Analysis

Genetic parameters such as major allele frequency (MAF), number of alleles (NA), genetic diversity (GD, often referred to as expected heterozygosity), observed heterozygosity (HO), and polymorphic information content (PIC) were measured by calculating the shared allele frequencies using PowerMarker software (v. 3.25) (Liu and Muse, 2005). The unweighted pair group method with arithmetic mean (UPGMA) dendrogram was implemented using MEGA software (v. 7.0) (Kumar, 2016), which is embedded in PowerMarker, with the UPGMA algorithm.

Results and Discussion

Development of Polymorphic Microsatellite Markers

We previously developed 17 polymorphic microsatellite markers and applied them both to analyze the genetic diversity of citrus genetic resources and to identify zygotic/nucellar individuals. However, the markers were not enough to discriminate all citrus genetic resources used in the study (Woo et al., 2019). Genome-wide characterization of microsatellite markers was reported in sweet orange (Citrus sinensis) previously (Biswas et al. 2014). We used marker information from the literature to further screen polymorphic microsatellites. To develop high-quality polymorphic markers, the microsatellite markers from sweet orange were applied to 11 citrus varieties belonging to six citrus groups: lemon, mandarin, sour orange, citron, orange, and tangor. We finally selected 36 polymorphic markers out of 74 microsatellite candidates. Table 1 summarizes 53 polymorphic nuclear microsatellite markers, including the 36 microsatellites developed in this study. The physical location of the 53 microsatellite loci on the nine pseudochromosomes was determined by performing a BlastN search against a reference genome of C. clementina cv. Clemenules (Wu et al., 2013; https://phytozome.jgi.doe.gov/pz/portal.html). The final microsatellite markers fully covered all of the pseudochromosomes of citrus (Fig. 1).

Table 1.

The 53 polymorphic microsatellite markers used in this study

No. Locus name Primer sequence (5' → 3') Repeat motif Tay
(°C)
Size range
(bp)
Reference
Forwardz Reverse
1 BM-CiSSR-012 TGTAAAACGACGGCCAGT
GGGCTCAGTTCTTCTCTACTC
GCATTAGGCTTCTCTCATACC (TTA)15 58 283-308 Woo et al., 2019
2 BM-CiSSR-013 TGTAAAACGACGGCCAGT
GGTGGCATACATACATACATACA
GCAACATCTGGAACTACTCA (TA)6 58 127-135
3 BM-CiSSR-032 TGTAAAACGACGGCCAGT
GCCTGAGTTTCTTTGTTATG
CATTCCATCGTCTCCTATTGT (TATG)4 58 136-172
4 BM-CiSSR-043 TGTAAAACGACGGCCAGT
ATTAGTGCGGGTAAGATGAA
AAGGATTTGGTGTAGGAAGTAA (AAAAT)3 58 286-327 Woo et al., 2019
5 BM-CiSSR-073 TGTAAAACGACGGCCAGT
CGGACAAGGAGATGAAGATAG
TTCTAACAGCACCAAGCAG (GA)16 58 319-345
6 BM-CiSSR-077 TGTAAAACGACGGCCAGT
TGTATTTATTTCTGACTACGACC
ATGCGTTTGGTGTGTGTT (AT)12 58 188-207
7 BM-CiSSR-082 TGTAAAACGACGGCCAGT
ACCTGAGCCCTTTTTGGTTT
GCCAGATCAAGGCTCAAATC (TC)13 58 150-155
8 BM-CiSSR-087 TGTAAAACGACGGCCAGT
CAGATCCTATTGCAGAGGCA
GCCCATTTGTATTGCCATTT (CAG)6 58 183-189
9 BM-CiSSR-093 TGTAAAACGACGGCCAGT
CCCCCTCTTCTTTCACACAA
GGTGAGCAGCCATCTTCTTC (TA)6 58 152-156
10 BM-CiSSR-094 TGTAAAACGACGGCCAGT
GAATTGGGAGGACGAACTGA
CGAGCCCTAGACAGAGATGG (AGA)7 58 268-277
11 BM-CiSSR-100 TGTAAAACGACGGCCAGT
GTTTTCAGCTGGATTCGAGG
CACGTGTCCTCCTGGAACTT (GCC)5 58 197-206
12 BM-CiSSR-111 TGTAAAACGACGGCCAGT
CCGATACAGCACAAAGCAAA
TGGAAAGAGAGAAGCCAAGC (AAT)7N15(AGC)7 58 134-143
13 BM-CiSSR-115b TGTAAAACGACGGCCAGT
CGGTGTGTATTGGGTACACG
GCTTTTTCGAAAGCGTCAAG (TA)17 58 231-250
14 BM-CiSSR-137 TGTAAAACGACGGCCAGT
GCAACGTGTACTGACGCTTG
GCTCGTATCTGAAGCTCGCC (TAT)7 53 301-327
15 BM-CiSSR-159 TGTAAAACGACGGCCAGT
ATGACCTCAAACGGTGAGCA
CTTCCACATCCGAACCGACA (GAGG)5 53 382-404
16 BM-CiSSR-162 TGTAAAACGACGGCCAGT
GCTAGGGTTCCAGACTTCCAG
GATTTGGCCGATCGAAAGCC (AAT)10(CAT)6 53 185-236
17 BM-CiSSR-165 TGTAAAACGACGGCCAGT
AGCAACTTAAGGTCCTTCACGA
TTCTCTGCTCTGCTGTGCAT (AAT)6 53 393-416
18 BM-CiSSR-201 TGTAAAACGACGGCCAGT
CAACAGTACCTGATGGTCCG
TTCTGAAATCCAGTCCCCTC (AAAAGA)6 55 259-270 In this study
19 BM-CiSSR-202 TGTAAAACGACGGCCAGT
CCCTCTTCAAGAACTGAGCC
CACCAGCTGTTTGCTGTTTT (AAAT)5 55 281-293
20 BM-CiSSR-203 TGTAAAACGACGGCCAGT
ACAACGCACCAAGTCAATGT
GTTGCGTCATCCATTTTGTC (AGCC)5 55 241-257
21 BM-CiSSR-204 TGTAAAACGACGGCCAGT
CCATGACCCACTTTCCCTAC
ATTCGGGTAGGTTGAAATCG (ACCCG)4 55 326-365
22 BM-CiSSR-208 TGTAAAACGACGGCCAGT
GGATGCTTGGCCTGATTTAT
ATTGTCACCGAAGCACCATA (TAA)7 55 340-352
23 BM-CiSSR-210 TGTAAAACGACGGCCAGT
GCCAGGATTGAAGGGTTTTA
TGTGAACAAGGGCAACAGAT (TTTAT)4 55 333-366
24 BM-CiSSR-217 TGTAAAACGACGGCCAGT
ATAATGGAAGCGTCGGATTC
GCCTAACGGCCAGAGTTTAC (CAG)10 55 313-327
25 BM-CiSSR-218 TGTAAAACGACGGCCAGT
TATGTCTACTGGTCGCAGGC
GTTGTCCCCTTGATACCACC (GGGAT)4 55 236-444
26 BM-CiSSR-221 TGTAAAACGACGGCCAGT
GGTCCTTTGGAGAAGGTTGA
CATGACCAAATGTCGGGTTA (TAAT)5 55 319-332
27 BM-CiSSR-224 TGTAAAACGACGGCCAGT
AACCCCTTGTCAAGTGATCC
TCTTCTTCAGTTGGTGCCTG (CAC)7 55 294-304
28 BM-CiSSR-225 TGTAAAACGACGGCCAGT
GTAAGGGGTTGTGAGGCAAT
CAACAGGTTTCGACCATGAC (GCT)8 55 322-353
29 BM-CiSSR-226 TGTAAAACGACGGCCAGT
ATTAAGGCTGGAAATGCCAC
ATTCTGCTGACGCTTCAATG (ATT)9 55 389-401 In this study
30 BM-CiSSR-230 TGTAAAACGACGGCCAGT
TCCATCAGCCATTCCATCTA
ATCTGAACCCTCCAATCCTG (TTC)9 55 276-302
31 BM-CiSSR-238 TGTAAAACGACGGCCAGT
ACTATGCGGCTCGAACTTTT
TCACCTTCACAACCGAACAT (CTT)11 55 269-277
32 BM-CiSSR-239 TGTAAAACGACGGCCAGT
ACATGCCATAGGAAGCAACA
CACCTTCTCATCAATCACGG (AAG)7 55 395-408
33 BM-CiSSR-240 TGTAAAACGACGGCCAGT
GCTGCTGCTGCTAGTTTGTC
AAAGATGGCAATGGGTTAGG (TCA)7 55 429-432
34 BM-CiSSR-241 TGTAAAACGACGGCCAGT
GGTCCTTTGGAGAAGGTTGA
CATGACCAAATGTCGGGTTA (TAAT)5 55 296-301
35 BM-CiSSR-243 TGTAAAACGACGGCCAGT
CCATCCCTGTAAATTCCACC
ATTGGTCGTTTCCTTTCCTG (AAAAT)4 55 319-323
36 BM-CiSSR-245 TGTAAAACGACGGCCAGT
TTTCCCAGGAGCTTACCAAG
TGCGTTCCATGGTCAGTATT (AAC)6 55 338-347
37 BM-CiSSR-246 TGTAAAACGACGGCCAGT
CCCTAGGGAAATTTGGGAAT
GCACTCGAGAGTTCTCGTTAAG (CAT)11 55 310-375
38 BM-CiSSR-247 TGTAAAACGACGGCCAGT
ATCTGTGTTTGGTCGCATGT
GGAAGATTACCGGACTTGGA (GAA)6 55 409-427
39 BM-CiSSR-248 TGTAAAACGACGGCCAGT
GCTCGGTTCTTGCATACTGA
GTCTGCAAACCCTGTTGATG (TGA)6 55 316-327
40 BM-CiSSR-249 TGTAAAACGACGGCCAGT
ATGGGCAAGAACAGGAAATC
CCATAGGATTTGCATGAGGA (GGA)6 55 321-331
41 BM-CiSSR-253 TGTAAAACGACGGCCAGT
AATTTCCTGCTCCAAACCAG
TCCAACAACTTGAACACGGT (TAA)14 55 319-355
42 BM-CiSSR-254 TGTAAAACGACGGCCAGT
TAAAATCCCTCGGAAACAGG
CTTTGCATGTTCAACGTTCC (ATC)6 55 234-313
43 BM-CiSSR-256 TGTAAAACGACGGCCAGT
CTCTCTGAACCTGACACCGA
TTTTCTCCACCCTTTCAACC (GAT)7 55 290-322
44 BM-CiSSR-258 TGTAAAACGACGGCCAGT
GGTAAGCACCTGCAAACTGA
ATTATGCAATTCCTCCTGGC (TATG)6 55 350-374
45 BM-CiSSR-260 TGTAAAACGACGGCCAGT
TCATCTGAACGGACCACAAT
TAACTGCACTTGCTTCCCTG (TTC)6 55 381-384
46 BM-CiSSR-262 TGTAAAACGACGGCCAGT
CAGTTTCATCCCACTGATGC
ACCAAGCGTCCTTAACAACA (ATT)6 55 181-205
47 BM-CiSSR-264 TGTAAAACGACGGCCAGT
AGGGGTGCTGAGCATAAAAT
ATACCCCGTCGTGGAATTAG (TAA)9 55 415-442
48 BM-CiSSR-266 TGTAAAACGACGGCCAGT
CGTAGCCAAAACTCCCAAAT
CCGAAGATGGAGGGAACTAA (GAA)8 55 293-342
49 BM-CiSSR-268 TGTAAAACGACGGCCAGT
TCTGTGGCTCACTTCACTCC
GAAGACGACAGATGCTGGAA (TCAC)7 55 355-365
50 BM-CiSSR-270 TGTAAAACGACGGCCAGT
TGCTGTAAGTGCAGTGCAAA
GGGACGAGCATCTTCCTTTA (TATG)5 55 342-347
51 BM-CiSSR-271 TGTAAAACGACGGCCAGT
CCCCCAAAATGCTGAGTAGT
AAAGGGAGAGAGTTGGCTGA (TATG)13 55 382-422
52 BM-CiSSR-272 TGTAAAACGACGGCCAGT
ATAGGTCCCCACAATGGAAA
GGGCATAAATGAATTGGGTC (GAA)8 55 405-419
53 BM-CiSSR-273 TGTAAAACGACGGCCAGT
GCATCATACGTTCAAGCCAC
TCTTGTGCTCTCCTGTGACC (CAT)12 55 298-336
zThe italicized letters in the forward primer indicate the M13 primer sequence.
yTa indicates annealing temperature.
http://static.apub.kr/journalsite/sites/kshs/2020-038-03/N0130380308/images/HST_38_03_08_F1.jpg
Fig. 1.

Physical map of 53 microsatellite loci on the nine pseudochromosomes of C. clementina cv. Clemenules. The underlined markers are 17 polymorphic microsatellites developed previously (Woo et al., 2019). Pseudo-chr. = pseudochromosome.

Identification of the Citrus Varieties Bred in Korea using Polymorphic Microsatellite Markers

Up to now, 34 citrus varieties were developed from bud sport mutants, nucellar mutants, and traditional genetic hybridizations by breeders at governmental institutes and breeding companies as well as private breeders in Korea (Table 2). Fifty-three microsatellite markers were applied to an available 32 Korean citrus varieties to determine their genotypes. Genetic characteristics of microsatellite loci based on the genotype analysis of 32 accessions are summarized in Table 3. A total of 245 alleles, ranging from 2 (BMCi-SSR084) to 11 (BMCi-SSR012) per locus, were observed among the 32 citrus accessions, with an average of five alleles per locus. Major allele frequency (MAF) varied from 0.22 (BMCi-SSR012) to 0.98 (BM-CiSSR-245). The average genetic diversity (GD) value was 0.53, ranging from 0.03 (BM-CiSSR-245) to 0.87 (BMCi-SSR012), and average polymorphism information content (PIC) value was 0.47, from 0.14 (BM-CiSSR-224) to 0.85 (BMCi-SSR012). The average observed heterozygosity (HO) was 0.47, with the lowest value in BM-CiSSR-245 and BM-CiSSR-270 (0.03) and the highest value in BM-CiSSR-262 (1.00).

Table 2.

Citrus varieties developed in Korea

Cultivar name Abbr. Breeding details Breeders
'Haryejosaeng' HRJ Nucellar mutant from C. unshiu 'Tachima Wase' CRI, NIHHSz
'Gaonhyang' n.a.* Bud sport mutant from Citrus hybrid 'Ehime Kashi 28 gou' Private breeder
'Gaeulhyang' GEH Citrus hybrid 'Ehime Kashi 28 gou' × Citrus hybrid 'Kanpei' ARES, JSSGPy
'Noeulhyang' NEH CRS0215 (Citrus hybrid 'Kiyomi' × Orange) × Osceola CRI, NIHHS
'Redsanta' RSN Citrus hybrid 'Ehime Kashi 28 gou' × C. reticulata 'Ponkan' HBIx
'R.O.Y.G' ARD Nucellar mutant from Citrus hybrid 'Ecriec 65' HBI
'Tarachogeuk' TRG Bud sport mutant from C. unshiu 'Nichinan 1 gou' HBI
'Moobong' MUB Citrus hybrid 'Shiranuhi' × C. hassaku CRI, NIHHS
'Minihyang' MNH C. kinokuni × C. reticulata 'Ponkan' CRI, NIHHS
'Sarahyang' SRH Nucellar mutant from Citrus hybrid 'Setoka' CRI, NIHHS
'Samdajosaeng' SMJ Nucellar mutant from C. unshiu 'Tachima Wase' CRI, NIHHS
'Sandojosaeng' SNJ Bud sport mutant from C. unshiu 'Sasaki unshiu' ARES, JSSGP
'Saebyeolbong' SBB Nucellar mutant from Citrus hybrid 'Shiranuhi' CRI, NIHHS
'Sunking' SNK Citrus hybrid 'Nankou' × C. reticulata 'Encore' CRI, NIHHS
Seolbongmi' SBM Citrus hybrid 'Kiyomi' × Citrus hybrid 'Seminole' CRI, NIHHS
'Sinyegam' SYG Citrus hybrid 'Kiyomi' × C. reticulata 'Wilking' CRI, NIHHS
'Suneat' SNE Bud sport mutant from Citrus hybrid 'Shiranuhi' Private breeder
'Winterprince' WTP Citrus hybrid 'Harehime' × C. reticulata 'Ootaponkan' CRI, NIHHS
'Injajosaeng' n.a.* Bud sport mutant from C. unshiu 'Takabayashi Wase' Private breeder
'Jeramon' JRM Nucellar mutant from C. limon 'Frost Lisbon' × C. limon 'Mayor' CRI, NIHHS
'Tamnaneunbong' TNB Nucellar mutant from Citrus hybrid 'Shiranuhi' CRI, NIHHS
'Tamnajoseang' TNJ Nucellar mutant from C. unshiu 'Shigeta unshiu' CRI, NIHHS
'Tamdo No. 1' TMD1 Citrus hybrid 'Kiyomi' × C. platymmama CRI, NIHHS
'Tamdo No. 3' TMD3 Citrus hybrid 'Kiyomi' × Citrus hybrid 'Seminole' CRI, NIHHS
'Tamdori' TDR Citrus hybrid 'Kiyomi' × C. reticulata 'Fortune' CRI, NIHHS
'Tambit No. 1' TMB1 Citrus hybrid 'Nishinokaori' × C. reticulata 'Ponkan' CRI, NIHHS
'Poonggwang navel' PGN Nucellar mutant from C. sinensis 'Washington navel' CRI, NIHHS
'Hayangjosaeng' HYJ Nucellar mutant from C. unshiu 'Ueno Wase' CRI, NIHHS
'Minimon' MNM Seedlings (C. limon 'Mayor') CRI, NIHHS
'Hallamon' HRM Seedlings (C. limon 'Mayor') CRI, NIHHS
'Jerajin No. 1' JRJ1 Citrus hybrid 'Ehime Kashi 28 gou' × C. reticulata 'Ponkan' JNw
'Jerajin No. 2' JRJ2 Citrus hybrid 'Ehime Kashi 28 gou' × C. reticulata 'Ponkan' JN
'Jerajin No. 3' JRJ3 Open pollination (C. reticulata 'Lee' as a female) JN
'Jerajin No. 4' JRJ4 Open pollination (C. reticulata 'Lee' as a female) JN
zCitrus Research Institute, National Institute of Horticultural & Herbal Science, RDA, Korea.
yAgricultural Research and Extension Services, Jeju Special Self-Governing Province, Korea.
xHannong Bio Industry Corp., Korea.
wJenong Co., Ltd., Korea.
*Not available.
Table 3.

Characteristics of 53 microsatellite loci based on the genotype analysis of 32 citrus varieties developed in Korea

Locus name SS NOBS Availability NG MAF NA GD HO PIC
BMCi-SSR012 32 32 1.00 13 0.22 11 0.87 0.34 0.85
BMCi-SSR013 32 30 0.94 6 0.52 3 0.59 0.23 0.50
BMCi-SSR032 32 32 1.00 7 0.72 7 0.46 0.44 0.43
BMCi-SSR043 32 31 0.97 5 0.69 4 0.46 0.06 0.40
BMCi-SSR073 32 32 1.00 8 0.58 6 0.59 0.66 0.54
BMCi-SSR077 32 31 0.97 4 0.81 4 0.33 0.35 0.31
BMCi-SSR082 32 32 1.00 5 0.69 4 0.46 0.41 0.39
BMCi-SSR084 32 32 1.00 3 0.63 2 0.47 0.25 0.36
BMCi-SSR093 32 32 1.00 2 0.77 2 0.36 0.47 0.29
BMCi-SSR094 32 31 0.97 7 0.65 4 0.51 0.58 0.45
BMCi-SSR100 32 32 1.00 7 0.45 4 0.64 0.59 0.57
BMCi-SSR111 32 32 1.00 5 0.59 4 0.51 0.31 0.41
BMCi-SSR115b 32 30 0.94 10 0.40 5 0.71 0.47 0.66
BMCi-SSR137 32 32 1.00 10 0.41 8 0.67 0.41 0.62
BMCi-SSR159 32 31 0.97 11 0.31 8 0.77 0.87 0.73
BMCi-SSR162 32 31 0.97 13 0.24 7 0.81 0.81 0.78
BMCi-SSR165 32 30 0.94 7 0.48 6 0.59 0.27 0.51
BM-CiSSR-201 32 32 1.00 6 0.77 5 0.39 0.38 0.36
BM-CiSSR-202 32 32 1.00 6 0.84 6 0.28 0.22 0.26
BM-CiSSR-203 32 32 1.00 8 0.66 5 0.54 0.50 0.51
BM-CiSSR-204 32 31 0.97 6 0.68 6 0.50 0.23 0.46
BM-CiSSR-208 32 32 1.00 5 0.83 3 0.30 0.22 0.28
BM-CiSSR-210 32 32 1.00 3 0.61 3 0.51 0.78 0.42
BM-CiSSR-217 32 32 1.00 5 0.81 4 0.33 0.31 0.31
BM-CiSSR-218 32 32 1.00 5 0.56 3 0.53 0.75 0.43
BM-CiSSR-221 32 32 1.00 6 0.53 4 0.55 0.50 0.45
BM-CiSSR-224 32 32 1.00 4 0.92 3 0.15 0.09 0.14
BM-CiSSR-225 32 32 1.00 8 0.58 6 0.60 0.47 0.55
BM-CiSSR-226 32 31 0.97 9 0.45 5 0.68 0.84 0.63
BM-CiSSR-230 32 29 0.91 14 0.31 7 0.79 0.93 0.76
BM-CiSSR-238 32 32 1.00 5 0.72 5 0.45 0.25 0.42
BM-CiSSR-239 32 32 1.00 6 0.61 4 0.52 0.44 0.44
BM-CiSSR-240 32 32 1.00 3 0.56 2 0.49 0.69 0.37
BM-CiSSR-241 32 32 1.00 6 0.72 4 0.43 0.44 0.38
BM-CiSSR-243 32 32 1.00 5 0.52 3 0.55 0.38 0.45
BM-CiSSR-245 32 32 1.00 2 0.98 2 0.03 0.03 0.03
BM-CiSSR-246 32 32 1.00 6 0.56 5 0.54 0.50 0.45
BM-CiSSR-247 32 32 1.00 4 0.64 3 0.52 0.53 0.46
BM-CiSSR-248 32 32 1.00 7 0.34 5 0.71 0.94 0.65
BM-CiSSR-249 32 32 1.00 7 0.50 5 0.61 0.56 0.54
BM-CiSSR-253 32 32 1.00 6 0.67 4 0.49 0.53 0.43
BM-CiSSR-254 32 32 1.00 5 0.50 3 0.57 0.44 0.47
BM-CiSSR-256 32 32 1.00 11 0.42 8 0.69 0.38 0.65
BM-CiSSR-258 32 32 1.00 8 0.53 5 0.65 0.84 0.61
BM-CiSSR-260 32 31 0.97 3 0.71 2 0.41 0.52 0.33
BM-CiSSR-262 32 32 1.00 2 0.50 3 0.52 1.00 0.40
BM-CiSSR-264 32 32 1.00 9 0.59 6 0.57 0.50 0.51
BM-CiSSR-266 32 31 0.97 4 0.50 3 0.52 0.45 0.40
BM-CiSSR-268 32 31 0.97 6 0.55 4 0.59 0.48 0.53
BM-CiSSR-270 32 32 1.00 3 0.52 3 0.51 0.03 0.40
BM-CiSSR-271 32 30 0.94 8 0.60 6 0.55 0.27 0.48
BM-CiSSR-272 32 32 1.00 11 0.39 6 0.74 0.72 0.70
BM-CiSSR-273 32 31 0.97 9 0.34 5 0.73 0.42 0.68
Mean 32 32 0.99 6 0.58 5 0.53 0.47 0.47
SS, sample size; NOBS, number of observations; availability is defined as 1-OBS/n, where OBS is the number of observations and n is the number of individuals sampled; NG, genotype number; MAF, major allele frequency; NA, number of alleles; GD, genetic diversity. GD, often referred to as expected heterozygosity, is defined as the probability that two randomly chosen alleles from the population are different; observed heterozygosity (HO) is simple proportion of heterozygous individuals in the population.; PIC, polymorphism information content.

A total of 245 alleles derived from the 53 polymorphic microsatellite loci were used to evaluate genetic relationships among the 32 varieties. A UPGMA dendrogram was constructed based on the genetic similarity matrices among the accessions. Fig. 2 illustrates the results of the cluster analysis based on microsatellite data. The resulting dendrogram revealed that the accessions used in the analysis could be distinctly classified into lemon and non-lemon groups. The microsatellite markers clearly discriminated most of the citrus varieties developed in Korea, except for ‘Tamnaneunbong’ (TNB), ‘Saebyeolbong’ (SBB), and ‘Suneat’ (SNE), which originated from nucellar offspring (TNB and SBB) and bud sport mutation (SNE) of Citrus hybrid ‘Shiranuhi’ (Table 2). Nucellar embryos develop from somatic embryos derived from maternal nucellar tissue surrounding the sexual embryo sac. This process is a kind of apomixis and is widely found in many citrus varieties. The offspring derived from nucellar embryony in citrus possesses the same genetic constitution as the female parent (Kepiro and Roose, 2007; Zhang et al., 2018). Our results indicate that somatic mutants, including nucellar offspring, originating from an identical parental plant have identical or very similar genetic constitutions to each other.

http://static.apub.kr/journalsite/sites/kshs/2020-038-03/N0130380308/images/HST_38_03_08_F2.jpg
Fig. 2.

UPGMA dendrogram based on genetic distances among 32 citrus varieties developed in Korea using 53 polymorphic microsatellite markers. Arrowheads indicate somatic mutant varieties originated from the Citrus hybrid ‘Shiranuhi’.

In conclusion, we developed 53 polymorphic microsatellite markers covering nine pseudochromosomes of citrus and applied them to the identification of citrus varieties bred in Korea. The microsatellite markers clearly discriminated most of the citrus varieties, whereas somatic mutant varieties that were derived by nucellar embryony or bud sport mutation from a parental plant showed identical genotypes on all loci investigated due to identical or very similar genetic constitution. The microsatellite markers developed in this study will be a useful molecular tool to protect breeders’ rights and guarantee the quality of nursery plants in the citrus industry.

Acknowledgements

This work was supported by the Golden Seed Project (Center for Horticultural Seed Development, No. 213007-05-4-WTP11), Ministry of Agriculture, Food and Rural Affairs (MAFRA), Ministry of Oceans and Fisheries (MOF), Rural Development Administration (RDA) and Korea Forest Service (KFS), and the Cooperative Research Program for Agriculture Science & Technology Development (Project No. PJ013445), RDA, Korea. Authors thank Dr. Si-Hyun Kim of Hannong Bio Industry Corp. and Mr. Ju Won Lee of Jenong Co., Ltd. for providing several citrus varieties.

References

1
Benavente-García O, Castillo J (2008) Update on uses and properties of citrus flavonoids: new findings in anticancer, cardiovascular, and anti-inflammatory activity. J Agric Food Chem 56:6185-6205. doi:10.1021/jf8006568
10.1021/jf800656818593176
2
Biswas MK, Xu Q, Mayer C, Deng X (2014) Genome wide characterization of short tandem repeat markers in sweet orange (Citrus sinensis). PLoS ONE 9:e104182. doi:10.1371/journal.pone.0104182
10.1371/journal.pone.010418225148383
3
Chang Y, Kim HB, Oh E-U, Yi K, Song KJ (2018) Construction of genetic linkage maps of 'Fina Sodea' clementine (C. clementina) and byungkyul (C. platymamma), a Korean landrace, based on RAPD and SSR markers. Hortic Environ Biotechnol 59:263-274. doi:10.1007/s13580-018-0021-3
10.1007/s13580-018-0021-3
4
Chung H, Lee J, Gil J, Um Y, Kim JH, Hwang MY, Kim HB, Hong CP, Park SG, et al. (2019) Development of polymorphic SSR markers from Pinus densiflora (Pinaceae) natural population in Korea. Plant Breed Biotechnol 7:67-71. doi:10.9787/PBB.2019.7.1.67
10.9787/PBB.2019.7.1.67
5
Donmez D, Simsek O, Izgu T, Kacar YA, Mendi YY (2013) Genetic transformation in Citrus. Scientific World J 2013:Article ID 491207. doi:10.1155/2013/491207
10.1155/2013/49120723983635PMC3745968
6
Iranshahi M, Rezaee R, Parhiz H, Roohbakhsh A, Soltani F (2015) Protective effects of flavonoids against microbes and toxins: the cases of hesperidin and hesperetin. Life Sci 137:125-132. doi:10.1016/j.lfs.2015.07.014
10.1016/j.lfs.2015.07.01426188593
7
Kepiro JL, Roose ML (2007) Nucellar embryony. In IA Khan, ed, Citrus: Genetics, Breeding and Biotechnology. CAB International, Oxfordshire, UK, pp 141-149. doi:10.1079/9780851990194.0141
10.1079/9780851990194.0141
8
Kim HB, Jeon JH, Han AR, Lee Y, Jun SS, Kim TH, Cho GH, Park PB (2012) Genetic evaluation of domestic walnut cultivars trading on Korean tree markets using microsatellite markers. Afr J Biotechnol 11:7366-7374
9
Kim HB, Uhm YK, Kim JJ, Lim S, Kim YM, Jung YS, Roh KH, Jang YS, Lee S, et al. (2016) Development of novel simple sequence repeat (SSR) markers from ramie (Boehmeria nivea L. Gaudich) and analysis of genetic diversity in its genetic resources. Hortic Environ Biotechnol 57:519-528. doi:10.1007/s13580-016-0094-9
10.1007/s13580-016-0094-9
10
Kim HJ, Park SH, Kim JH, Yim B, Mun JH, Kim HB, Hur YY, Yu HJ (2019) An efficient strategy for developing genotype identification markers based on simple sequence repeats in grapevines. Hortic Environ Biotechnol 60:363-372. doi:10.1007/s13580-019-00123-x
10.1007/s13580-019-00123-x
11
Kumar S, Stecher G, Tamura K (2016) MEGA7: Molecular Evolutionary Genetics Analysis version 7.0 for bigger datasets. Mol Biol Evol 33:1870-1874. doi:10.1093/molbev/msw054
10.1093/molbev/msw05427004904
12
Liu KJ, Muse SV (2005) PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 21:2128-2129. doi:10.1093/bioinformatics/bti282
10.1093/bioinformatics/bti28215705655
13
Schuelke M (2000) An economic method for the fluorescent labeling of PCR fragments. Nat Biotechnol 18:233-234. doi:10.1038/72708
10.1038/7270810657137
14
Talon M, Gmitter FG (2008) Citrus genomics. Inter J Plant Genomics. Article ID 528361. doi:10.1155/2008/528361
10.1155/2008/52836118509486PMC2396216
15
Food and Agriculture Organization of the United Nations (FAO) (2018) http://www.fao.org/faostat/en/#data/QC. Accessed 03 Feb. 2018
16
Woo JK, Park YC, Lee JW, Yun SH, Kim M, Park S, Lee Y, Song KJ, Kim HB (2019) Evaluation of polyembryony for genetic resources and efficacy of simple sequence repeat markers for the identification of nucellar and zygotic embryo-derived individuals in citrus. Appl Biol Chem 62:30. doi:10.1186/s13765-019-0437-1
10.1186/s13765-019-0437-1
17
Wu GA, Prochnik S, Jenkins J, Salse J, Hellsten U, Murat F, Perrier X, Ruiz M, Scalabrin S, et al. (2013) Sequencing of diverse mandarin, pummelo and orange genomes reveals complex history of admixture during citrus domestication. Nat Biotechnol. 32:656-662. doi:10.1038/nbt.2906
10.1038/nbt.290624908277PMC4113729
18
Zhang S, Liang M, Wang N, Xu Q, Deng X, Chai L (2018) Reproduction in woody perennial Citrus: an update on nucellar embryony and self‑incompatibility. Plant Reprod 31:43-57. doi:10.1007/s00497-018-0327-4
10.1007/s00497-018-0327-429457194
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