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Research Article

Development of 34 New Microsatellite Markers from Actinidia arguta: Intra- and Interspecies Genetic Analysis

Soon-Jae Kwon1, Gi-An Lee2, Yong-Bum Kwack3, Ho-Sun Lee2, Gyu-Taek Cho2, Ho-Cheol Ko2, Sok-Young Lee2, Yeon-Gyu Kim2, Kyung-Ho Ma2,*
Plant Breeding and Biotechnology 2013;1(2):137-147.
Published online: June 30, 2013

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*Corresponding author: Kyung-Ho Ma, khma@korea.kr, Tel: +82-31-294-6029, Fax: +82-31-294-6029
• Received: June 15, 2013   • Revised: June 21, 2013   • Accepted: June 23, 2013

Copyright © 2013 The Korean Society of Breeding Science

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  • The present study investigated the isolation and characterization of 34 polymorphic microsatellite markers developed from Actinidia arguta (Sieb. and Zucc.) Planch. ex Miq. var arguta. These markers produced 349 alleles in eight Actinidia species, with an average of 10.3 alleles per locus. Observed heterozygosity ranged from 0.50 to 0.87 (mean = 0.72), and polymorphism information content ranged from 0.37 to 0.88 (mean = 0.69). The phylogenetic relationship obtained using microsatellite markers showed minor clustering and population differences among species while 38 A. arguta accessions fell into two subgroups. These newly developed polymorphic microsatellite markers will be very useful in sustainable genetic conservation, marker-assisted breeding, and classification of the Actinidia genus.
  • Key words: Microsatellites, Actinidia arguta, Genetic diversity
The genus Actinidia comprises 76 species and about 120 taxa of perennial, dioecious, viny, and deciduous fruit trees. Actinidia species have a wide range of distribution in eastern Asia that includes tropical equatorial and temperate regions (Ferguson and Huang 2007). Four of the 76 species have been domesticated as fruit crops: A. deliciosa, A. chinensis, A. arguta, and A. eriantha (Cui et al. 2002; Ferguson 1990). A. deliciosa (A. Chev.) C. F. Liang and A. R. Ferguson var. deliciosa is a green-fleshed kiwifruit, and A. chinensis Planch. var. chinensis is yellow-fleshed. Kiwifruit production has increased remarkably since the introduction of A. deliciosa seeds to New Zealand in the early 1900s, reaching more than one million tons in 2000 (Huang and Ferguson 2001).
Four Actinidia species, A. arguta, A. kolomikta, A. polygama, and A. rufa, are found in Korea (Cui et al. 2002; Ferguson 1990; Kim et al. 2003). A. arguta (Sieb. and Zucc.) Planch. ex Miq. var. arguta grows in the wild in mountainous and hilly terrain throughout Korea; it is tolerant to freezing and is resistant to various harmful insects. Because the exterior of the fruit is soft, smooth, and leathery, it can be eaten whole without peeling (Williams et al. 2003). Given its richness in various minerals and vitamin C, this fruit is commonly used in soft drinks and jams. It is also used as an anodyne, diuretic, antifebrile, and thirst-quencher in home remedies (Lee et al. 2004). Despite these beneficial traits and uses, commercial cultivars of A. arguta have not been available, and most plants are growing in the wild without much improvement. Although several attempts have been made to introduce the genes from A. arguta into A. deliciosa (Kim et al. 2008; Lee et al. 2004), the hybrids have not yet been widely accepted.
The A. arguta accessions have not been subjected to genetic diversity analysis. For the conservation and sustainable use of wild accessions, it is important to understand the genetic variation, genetic structure, and mating systems of natural populations. Given their high levels of polymorphism with codominance and their excellent reproducibility, microsatellite or simple-sequence repeat (SSR) markers have been preferred for use in the analysis of molecular diversity in conservation biology and molecular ecology (Park et al. 2009). Although microsatellite markers have been developed in the Actinidia species, this development has been restricted to the commercial species A. chinensis and A. deliciosa and has not included A. arguta (Huang et al. 1998; Korkovelos et al. 2003). Huang et al (1998) demonstrated that 40 microsatellite markers derived from the genomic library of A. chinensis were successful in the genomic DNA of A. arguta. Another study (Fraser et al. 2000) found that four of nine microsatellite markers derived from the genomic library of A. deliciosa were successful in the polymerase chain reaction (PCR) amplification of A. arguta accessions. The same group of researchers subsequently tested cross-species amplification among 21 Actinidia species with 20 expressed sequence tag (EST)-derived microsatellite markers (Fraser et al. 2005). Three of these markers failed in amplification, and three others were inconsistent in the amplification of A. arguta (4x) accessions.
In an effort to preserve the genetic diversity of A. arguta in Korea, we collected wild accessions throughout the country and stored the seeds in a short-term preservation facility. The seeds were screened for genetic redundancy before they were placed in a long-term storage facility. Because microsatellite markers are preferred for genetic diversity analysis, we developed microsatellite markers from the A. arguta genomic library. This report describes the new set of markers for genetic diversity analysis in Actinidia species and possible markers for sex determination in A. arguta.
Plant materials and genomic DNA extraction
A total of 91 accessions from eight Actinidia species were used in this study (Table 1). The young leaves were acquired from Namhae Sub-Station of National Institute of Horticultural & Herbal Science which conserved diverse accessions of Actinidia species in experimental field. Total genomic DNA was extracted from grinded power of young leaves by liquid nitrogen using the Plant DNAzol® Reagent (Invitrogen, Carlsbad, CA, USA), following the supplier’s protocols. The extracted DNA was quantified using an ultraviolet-visible (UV-Vis) spectrophotometer (ND-1000; NanoDrop, Wilmington, DE, USA).
Construction of an SSR motif-enriched library
A modified biotin-streptavidin capture method was used to construct an SSR motif-enriched library of A. arguta (Sieb. and Zucc) Planch. ex Miq. var. arguta genomic DNA (Kwon et al. 2005). Genomic DNA samples (10 μg) were digested with seven blunt-end–producing restriction enzymes (EcoRV, DraI, SmaI, PvuI, AluI, HaeIII, RsaI). The fully digested DNA samples were pooled and size-fractionated on 1.4% agarose gels. DNA fragments of 300 bp to 1,500 bp were eluted from the gels and were purified using a gel extraction kit (Qiagen, Hilden, Germany). Approximately 1 μg of DNA fragments was ligated with 1 μg of the double-stranded adaptor (AP11/AP12). The adaptor was prepared by mixing equal molar amounts of oligonucleotides AP11 (5′CTC TTG CTT AGA TCT GGA CTA-3′) and AP12 (5′-TAG TCC AGA TCT AAG CAA GAG CAC A-3′), heated to 94°C, then cooled to 25°C over a period of 4–5 h. Preamplification of adaptor-ligated DNA fragments was performed for 15 cycles of PCR in a 50-μl reaction volume with a single primer (AP11) and an annealing temperature of 56°C. The preamplified products were hybridized with a mixture of long (40–45 nucleotides) biotin-labeled repeat probes. Hybridization was performed for 2 h at 65°C in a reaction mixture (50 μl) that included 6× standard sodium citrate (SSC), 0.1% sodium dodecyl sulfate (SDS), ~100 ng of preamplified product, and 300 ng of each biotin-labeled oligo: (GA)20, (CA)20, (AGC)15, (GGC)15, (AAG)15, (AAC)15, and (AGG)15. The hybridized DNA fragments were captured with 400 μg of streptavidin-coated magnetic beads (Promega, Madison, WI, USA) by incubating the mixture at 65°C with gentle agitation for 30 min. The beads were separated from the liquid using a magnetic stand (Promega) and were washed five times in 300 μl 6× SSC/0.1% SDS (1× SSC = 150 mM NaCl, 15 mM sodium citrate, pH 7.0) at room temperature with gentle agitation. After stringent washing, all samples were briefly washed in 5× SSC to remove the SDS, and DNA fragments were eluted with 50 μl of dH2O at 90°C for 5 min. Final elutions (5 μl) were amplified for 15 cycles of PCR using the AP11 primer. After checking the gel, the amplified DNA products were cloned into pGEM-T Easy Vector (Promega) and were transformed into Escherichia coli cells through electroporation. Recombinant colonies were identified by blue or white colony selection on lysogeny broth (LB) plates containing ampicillin, 5-bromo-4-chloro-3-indolyl-b-D-galactopyranoside (X-gal), and isopropyl β-D-1-thiogalactopyranoside (IPTG).
DNA sequencing and SSR primer design
A total of 762 white colonies were randomly selected from the enriched library. Plasmid DNA was purified with the QIAprep Spin Miniprep Kit (Qiagen), and nucleotide sequencing was performed using an ABI 3100 DNA sequencer with a BigDye terminator kit (Applied Biosystems, Foster City, CA, USA). SSR motif elucidation and primer design were performed using the ARGOS program (Kim 2004).
PCR amplification
The “M13 tail at its 5′ end” PCR method was used to measure the size of the PCR products (Schuelke 2000). PCR amplification was performed in a total volume of 20 μl containing 2 μl of genomic DNA (10 ng/μl), 0.2 μl of the specific primer (10 pmol/μl), 0.4 μl of M13 universal primer (10 pmol/μl), 0.6 μl of normal reverse primer, 2.0 μl of 10× PCR buffer (Takara, Tokyo, Japan), 1.6 μl of deoxynucleoside triphosphate (dNTP; 2.5 mM), and 0.2 μl of Taq polymerase (5 unit/μl; Takara). The PCR amplification conditions were as follows: 94°C for 3 min, followed by 30–33 cycles at 94°C (30 s), 50–55°C (45 s), 72°C (45 s), then 15 cycles at 94°C (30 s), 53°C (45 s), and 72°C (45 s), and final extension at 72°C for 20 min. PCR was performed in PTC-220 thermocyclers (MJ Research, Waltham, MA, USA). The PCR products of three microsatellites were mixed together in a ratio of 6-FAM:HEX:NED (fluorescent dyes) = 1:3:4, which varied depending on the amplification intensity for individual markers as determined on an ABI PRISM 3130xl genetic analyzer (Applied Biosystems). PCR products labeled with HEX and NED were added in greater amounts, and those labeled with FAM were added in lesser amounts to match the different signal intensities of these fluorescent dyes. The 1.5 μl mixed PCR product was combined with 9.2 μl of Hi-Di formamide and 0.3 μl of an internal Genescan-500 ROX (6-carbon-X-rhodamine) molecular size standard (35–500 bp). The samples were denatured at 94°C for 3 min and were analyzed with the ABI PRISM 3130xl. Base-pair molecular weights of the microsatellite products were estimated with Genescan software (ver. 3.7; Applied Biosystems) using the local Southern method. The individual fragments were assigned as alleles of the appropriate microsatellite loci with Genotyper software (ver. 3.7, Applied Biosystems).
Data analysis
The PowerMarker version 3.25 (Liu and Muse 2005) and GenAlEx version 6.1 (Peakall and Smouse 2006) programs were used to measure variability at each locus, observed heterozygosity (HO), gene diversity/expected heterozygosity (HE), and polymorphism information content (PIC). The number of alleles (A) and PIC values were calculated with the equation of PIC=1−∑P2i−∑2 P2i P2j where ∑P2i is the sum of each squared ith haplotype frequency (Botstein et al. 1980). A phylogenetic dendrogram was constructed using the unweighted pair-group method with arithmetic averages (UPGMA) with PowerMarker (Liu and Muse 2005) and MEGA4 (Tamura et al. 2007) software.
Intra- and interpopulational levels of genetic variation identified by the cluster analysis were estimated from allelic frequencies using analysis of molecular variance (AMOVA) (Weir 1996; Weir and Cockerham 1984). Pairwise estimates of the correlation of alleles within subpopulations (FST) were calculated for subpopulations using an AMOVA approach in GenAlEx (Peakall and Smouse 2006).
Development of SSR markers from A. arguta
A total of 762 clones were randomly picked from the primary transformation plates and were sequenced (Table 2). After excluding redundant clones (n = 35) and truncated clones with SSR motifs near their ends (n = 162), 565 clones were analyzed for primer designing. Of these, 140 clones were suitable for designing primer pairs for PCR amplification of the SSR motifs. Clones containing <12 nucleotides in the SSR motifs were not included in the primer design. Dinucleotide repeat-motif–containing clones were predominant (86.1%) among the 565 clones, with 864 dinucleotides, 87 trinucleotides (8.7%), and 53 tetranucleotides or more (5.8%) clones (Table 3).
Variation among Actinidia accessions
SSR variations were sought using the 140 selected primer pairs with a core collection of 91 Actinidia accessions representing diverse regions and species (Table 1). This collection is maintained at the National Institute of Horticultural & Herbal Science (RDA, Korea). Intra- and interspecies accession polymorphisms were present in 34 primer pairs (Supplementary Table 1). The number of repeating units among these polymorphic SSR loci varied from 6 to 23, and the length of the repeat region varied from 12 bp in GB-AA-017 [(CT)6] to 174 bp in GB-AA-065 [(GA)11(GAA)23] (Table 4). Whereas 26 (82.6%) polymorphic loci contained di-nucleotide repeating motifs, only three (6.5%) and five (10.9%) polymorphic loci had tri- and tetranucleotides or greater repeating motifs, respectively (Table 3). With these 34 SSRs, a total of 349 alleles were detected among the Actinidia species accessions, resulting in an average of 10.3 alleles per locus (Table 4). The GB-AA-393 primer pair produced the highest number of alleles (n = 20) and also had a high PIC value (PIC = 0.88), whereas GB-AA-017 produced only two alleles (PIC = 0.37). The major allele frequency (MAF) ranged from 0.22 to 0.65, with a mean value of 0.39. The observed heterozygosity (Ho) ranged from 0.50 to 0.87 (mean = 0.72), and the expected heterozygosity (He) ranged from 0.00 to 1.00 (mean = 0.55). Considering three species (A. arguta, A. chinensis, A. deliciosa) individually, A. deliciosa showed the most variation (PIC = 0.44) and A. chinensis (PIC = 0.41) showed the least variation in all diversity denominators (data not shown).
Intra- and interspecies relationships obtained from SSR profiles
Proportions of shared alleles were used to calculate genetic distances between all pairwise combinations among the 91 Actinidia accessions used in this study. A phylogenetic dendrogram based on the SSR profiles clearly shows two major groups at a genetic distance of 0.45 (Fig. 1). The first group (GI) comprised A. chinensis, A. deliciosa, A. eriantha, A. kolomikta, A. macrosperma, and A. rufa. The accessions of the four latter species (A. eriantha, A. kolomikta, A. macrosperma, and A. rufa) did not form a subspecific clade, but were intermixed in each GI clade. The GII clade included A. arguta was clearly distinguished from first group (GI) and formed two major subclades at a genetic distance of 0.25.
In this study, 762 DNA sequences of A. arguta were retrieved from a microsatellite-enriched library, but only 140 (18.4%) were used to design the SSR primers. The majority of DNA sequences (81.6%) were not suitable for primer design; 55.8% had SSRs at the 5′ or 3′ end and fewer than 12 nucleotides in the SSR motifs; and 4.6% were duplicate or redundant DNA sequences (Table 2). This result was consistent with those reported for Sorghum bicolor and cassava (Manihot esculenta Crantz), wherein 70% and 45% of the clones, respectively, had SSRs too close to the cloning sites at the 5′ or 3′ end (Mba et al. 2001; Taramino et al. 1997). Similarly, redundant DNA sequences consisting of the same SSR locus or showing more than 95% similarity in flanking sequences were found in 20% of cassava accessions (Mba et al. 2001), 16% of perennial ryegrass (Lolium perenne L.) accessions (Jones et al. 2001) and 2.2% in avocado (Persea americana Mill.) accessions (Ashworth et al. 2004). Most redundancies were due to cloning, locus duplication, or allelism and were from the same microsatellite enrichment library. Ashkenazi et al (2001) also reported that some conserved potato (Solanum phureja Juz. & Buk.) DNA sequences flanking microsatellite regions were too short to permit the design of an appropriate primer. Earlier studies reported that the AT/TA repeat was the most frequent type of SSR in plants, followed by the AG/GA/TC/CT repeat (Danin-Poleg et al. 2001; Wang et al. 1994; Yu et al. 1999). In this study, the most frequent type of microsatellite repeat was AG/GA/TC/CT (60.1%), followed by AC/CA/TG/GT (23.7%), AAG/AGA/GAA (4.4%), and AT/TA (2.2%; Table 3). However, the frequency of a microsatellite repeat may vary with species and genus. For instance, Ashworth et al (2004) reported that AG and ATG were the most frequent repeats in avocado.
The SSR genetic diversity observed among Actinidia accessions in our study can be compared to the diversities among A. chinensis and A. deliciosa that have been measured using other SSR sets (Korkovelos et al. 2008). The average numbers of alleles and PIC in our analysis were 10.3 and 0.69, respectively. Similarly, Korkovelos et al. (2008) reported averages of 7.8 ± 3.2 alleles and PIC = 0.739 ± 0.158. These values are higher than those detected in cucumber (Cucumis; average 2.4 alleles/locus, PIC = 0.28) and common buckwheat (Fagopyrum; average 5.9 alleles/locus, PIC = 0.48) (Danin-Poleg et al. 2001; Ma et al. 2009). Thus, the SSR markers among 91 Actinidia accessions in the present study were effective for assessing genetic diversity and for understanding population structure.
The species relationship derived from our cluster analysis is consistent with other reports (Huang et al. 2002; Li et al. 2002). In particular, the clustering results confirmed the previously established close relationship between A. deliciosa and A. chinensis (Cipriani et al. 1998; Huang et al. 1997; Testolin and Ferguson 1997), revealing A. chinensis as a progenitor of A. deliciosa (Cipriani et al. 1998). Others have considered A. arguta to be promising for the development of cultivars (Ferguson 1999; Nishiyama 2007). These major species were unambiguously classified into two groups in the present study. However, A. kolomikta and A. macrosperma were included in Group I in our analysis. This result contrasts with a previous analysis using RAPD markers that placed these species with A. arguta (Huang et al. 2002). This result also contrasts with a study using matK gene and internal transcribed spacer (ITS) sequences that found a lesser genetic distance between these species and A. arguta than with other groups (Li et al. 2002). The morphological features of A. kolomikta and A. macrosperma are also more similar to those of species in the A. arguta group (Ferguson 1990) than to those of other groups. The grouping result may be due to the limited amplification of transferability in SSR markers. Although most Actinidia species were successfully amplified with all 34 SSR markers, the amplifications of transferability in A. kolomikta and A. macrosperma were 80% and 57%, respectively. The transferability of SSRs to other Actinida species showed average value of 77% ranged from 57% (A. macrosperma) to 90% (A. chinensis). A little higher transferability than other genus such as Prunus (mean=59%) and Allium (mean=59%) reveals that genetic distances are relatively low between tested Actinidia species (Lee et al. 2011; Wang et al. 2012).
These newly developed polymorphic microsatellite markers will be very useful for selection in marker-assisted breeding, genetic conservation, and classification of the Actinidia genus. The sex-related markers identified in our study are also of major importance to kiwifruit breeders and the produce industry because they allow the distinction of female plants at the seedling stage and have great potential utilization in marker-assisted selection in this species.
PBB-01-137-suppl.xlsx
This study was supported by the Rural Development Administration (RDA), a grant (Code # PJ008564) from the National Academy of Agricultural Science, RDA, Republic of Korea.
Fig. 1
Phylogenetic dendrogram of the varieties and species in Actinidia based on SSR amplification profiles.
pbb-01-137f1.jpg
Table 1
List of Actinidia species used in this study.
Table 1
Taxon Number of accessions Variety Geographic location
A. arguta (Sieb. and Zucc.) Planch. ex Miq. var. arguta 40 63. K5-1-22 73. K5-3-6 83. K5-4-12 93. K5-10-1 Korea
64. K5-2-3 74. K5-3-7 84. K5-5-1 94. K5-10-2
65. K5-2-7 75. K5-3-8 85. K5-5-8 95. K5-10-3
66. K5-2-8 76. K5-3-12 86. K5-5-12 96. K5-10-5
67. K5-2-10 77. K5-3-13 87. K5-5-14 97. K5-10-8
68. K5-2-13 78. K5-3-18 88. K5-6-10 98. K5-11-1
69. K5-2-16 79. K5-4-3 89. K5-6-12 99. K5-11-2
70. K5-2-18 80. K5-4-7 90. K5-9-1 100. K5-11-3
71. K5-2-22 81. K5-4-8 91. K5-9-4 101. K5-11-8
72. K5-3-3 82. K5-4-10 92. K5-9-8 102. K5-12-6
A. chinensis Planch. var. chinensis 13 14. SKK3 20. SKK10 104. Red-Kiwi 106. Jesi-Gold Korea
16. SKK5 21. SKK11, 105. Hort16A
17. SKK7 (Gracies) 23. SKK13, 108. Yeo-San-Hyang
19. SKK9 (Chin Mei) 62. Jeju-Gold 115. Guem-Goi
A. chinensis Planch. var. chinensis 6 12. SKK1 30. S13 China
13. SKK2 15. SKK4 18. SKK8 (Tomuri) 117. SKK12-2
A. deliciosa (A. Chev.) C.F. Liang and A.R. Ferguson var. deliciosa 25 1. Abbott 7. Hyang-Rok 11. Yellow Queen (First Emperor) 45. SKK 60 New Zealand, Japan, China
2. Bruno 8. Golden King 38. SKK22 (Jinkui) 47. SKK80 (Red Princess)
3. Hayward 9. Golden Yellow 40. SKK33 (Wha-Pyung 2 Ho) 116. Jin-Mi
4. Monty 10. Sensation Apple 42. SKK43 (Seo-Hyang)
5. Matua 37. SKK18 (Chieftain) 43. SKK44 110. M51-2
6. Tomuri 39. SKK23 46. SKK 61
34. Sun-WuKong 41. SKK34 (Mi-Lyang 2 Ho) 109. M51-1
A. eriantha Benth. 3 50. S10 51. S20 103. Bi-Dan China, Korea
A. arguta var. purpurea (Rehd.) C.F. Liang 1 24. S3 China
A. kolomikta (Maxim. and Rupr.) Maxim. 1 25. S4 China
A. macrosperma C.F. Liang 1 27. S7 China
A. rufa (Sieb. and Zucc.) Planch. ex Miq. 1 61. Seom-Darae Korea
Table 2
Efficiency of the procedure adopted for the identification of microsatellite markers in A. arguta.
Table 2
Procedural step Number (percentage)
Sequenced clones 762
Redundant clones 35 (4.6%)
Unique clones 727 (95.4%)
SSR clones 565 (74.1%)
Truncated clones (5′ or 3′ end) 162 (21.3%)
Fewer than 12 nucleotides 263 (34.5%)
Primer pairs designed 140 (18.4%)
Polymorphic loci 34 (24.3%)z)

z)percentage based on the designed primer pairs.

Table 3
Frequency and type of di-, tri- and ≥ tetra-nucleotide repeats isolated from the A. arguta microsatellite-enriched library.
Table 3
Repeat unit Repeat class Number of microsatellite loci Polymorphic loci
Number Percentage Number Percentage
Di-nucleotide AC/CA/TG/GT 238 23.7% 8 17.4%
AG/GA/TC/CT 603 60.1% 30 65.2%
AT/TA 22 2.2%
CG/GC 1 0.1%
Total 864 86.1%
Tri-nucleotide AAC/ACA/CAA 15 1.5%
AAG/AGA/GAA 44 4.4% 1 2.2%
AAT/ATA/TAA 4 0.4%
ACC/CCA/CAC 3 0.3%
AGC/CGA/GAC 4 0.4%
AGG/GGA/GAG 14 1.4% 2 4.3%
ATC/TCA/CAT 1 0.1%
CCG/CGC/GCC 2 0.2%
Total 87 8.7%
≥ Tetra-nucleotide 53 5.8% 5 10.9%
Total repeat motifs 1004 46
Table 4
Characteristics of 34 polymorphic microsatellite loci for Actinidia species.
Table 4
Marker GeneBank accession Repeat motif Primer sequence Size (bp) Ta (°C) A MAF He Ho PIC
GB-AA-005 FJ647762 (CT)17 F: AGTTGTGCATCCAAAGGC
R: CAGTGGGGTGAAGAACGA		 192–218 57 12 0.32 0.73 0.78 0.76
GB-AA-012 FJ647763 (TG)13 F: TCACAACACTCATTTCGGC
R: ATCCGCTTCCTTAGCTGC		 154–176 58 10 0.49 0.47 0.71 0.68
GB-AA-015 FJ647764 (AG)19 F: CCTGGTCGTTCAGGGAAT
R: ATGGCATTTGTTGCCTTG		 267–293 58 14 0.24 0.89 0.83 0.83
GB-AA-017 FJ647765 (CT)6 F: AAAGTGTGAGCACGTGACAA
R: TGAGAGAGAGAGGTGGCG		 170–182 58 2 0.54 0.00 0.50 0.37
GB-AA-018 FJ647766 (CA)8, (GGA)4 F: ACCATGGCACAGATGGAA
R: TCCAGTGCCTTTTTAAGCC		 147–171 58 11 0.23 0.75 0.81 0.80
GB-AA-024 FJ647767 (GA)19 F: AGGAGACCCAACAGGAACA
R: AATTCGGGTCACCACACA		 155–181 58 12 0.40 0.49 0.75 0.74
GB-AA-054 FJ647768 (GA)15 F: ACCAAAAACCACCTGCCT
R: TGAACCCGTATTCGCATC		 186–214 58 15 0.23 0.87 0.85 0.84
GB-AA-065 FJ647769 (GA)11(GAA)23 F: ATTGAAGCCCCCATTGAG
R: CCAAGGAGGGCATTTAGG		 212–238 58 11 0.43 0.60 0.74 0.72
GB-AA-069 FJ647770 (GGGA)6(GA)8 F: CGTTCTCCTTCGACCCTT
R: CCGTTACCTTGTCCAATCC		 196–258 58 11 0.43 0.67 0.74 0.71
GB-AA-080 FJ647771 (GA)15 F: CCAATCAACAAGATGCACG
R: TGGGAGGTTGAAACTGGA		 179–213 58 11 0.26 1.00 0.82 0.80
GB-AA-084 FJ647772 (GA)15 F: CATTCGAACCAACGCAAT
R: AGTCGGAGCTGGGAGAAG		 233–259 58 12 0.22 0.96 0.83 0.82
GB-AA-088 FJ647773 (CT)7 F: TCTGGTTTGTTTTCCACCA
R: GGTTGAGTTCCATTCCCG		 177–197 57 8 0.45 0.56 0.69 0.67
GB-AA-091 FJ647774 (CT)19 F: TGACTTAAGGGCGACCAA
R: GGAAATCGCTCATGGACA		 201–223 58 8 0.38 0.62 0.74 0.69
GB-AA-094 FJ647775 (AC)15 F: ACAGGGGAACATCAGTGC
R: GTGGGATATAACCGGGGA		 208–220 57 6 0.38 0.41 0.68 0.63
GB-AA-096 FJ647776 (GA)6, (GA)3 F: TTGGTACACAAGACGCCC
R: GAAATTTCTTCACCCGCC		 229–235 58 3 0.52 0.01 0.50 0.39
GB-AA-302 FJ647777 (AG)13 F: TCGGTGATAAATGGCAGG
R: GGCTCCTTGACAGCACAG		 269–311 58 11 0.43 0.31 0.74 0.72
GB-AA-303 FJ647778 (CT)15 F: TGGGGCATTTATGCCTAT
R: TCCAACCTTCTTGGCTCA		 156–258 57 12 0.33 0.35 0.75 0.73
GB-AA-304 FJ647779 (AG)11 F: CAGTCCACAAAATGGGTCA
R: GGTGAACACCCCCAAAGT		 202–364 58 13 0.41 0.15 0.67 0.64
GB-AA-308 FJ647780 (CCCT)4, (GGGT)2, (GGGT)2 F:TAGTGCTGCGAAGGAGGA
R: ATTGCACCATTCTGTGGC		 265–304 58 8 0.32 0.36 0.77 0.75
GB-AA-331 FJ647781 (GA)15, (CAGA)4 F: CCATCTTTTTGTGCCTTTG
R: TTGTTGGTATCATGCCCC		 259–303 57 13 0.28 0.59 0.83 0.80
GB-AA-333 FJ647782 (TG)12 F: AAGTTCATTCCACGCACG
R: ATTGCATTTGAGCCGCTA		 242–276 58 6 0.49 1.00 0.67 0.61
GB-AA-337 FJ647783 (GA)10, (AC)6 F: TTCTCTGCGCGTTCTCTC
R: AGCCTCAACCAAGAAGGG		 290–332 58 10 0.36 0.53 0.74 0.72
GB-AA-340 FJ647784 (CCT)5 F: AAGGAATTCGCCCTCAAA
R: GGCTGACAAGAAGCGATG		 287–296 58 4 0.65 0.68 0.49 0.45
GB-AA-342 FJ647785 (GA)2, (GA)4 F: AAAATTCCAATTCCCCCA
R: CATTTCGGAATCCCCTTT		 261–293 57 13 0.35 0.59 0.81 0.80
GB-AA-343 FJ647786 (AG)14 F: TGCTTCTTCGGTCATGCT
R: CACCATTTCGAACCCAGA		 232–262 58 5 0.44 0.67 0.70 0.64
GB-AA-356 FJ647787 (AC)12 F: CCCGACTTCCAAGTCTCC
R: CTCCGGATGCCCTTTATC		 251–287 58 16 0.25 0.70 0.85 0.83
GB-AA-366 FJ647788 (GA)7 F: CAGCTCCAAGGGCTATGA
R: TGTTCCCACTACCGCAAC		 241–247 57 5 0.51 0.09 0.53 0.43
GB-AA-369 FJ647789 (CT)16(CA)17 F: TGATCCACAACGTCATCAA
R: GGGCACGCTAGACACACC		 185–215 58 13 0.32 0.31 0.76 0.74
GB-AA-370 FJ647790 (GA)16 F: GGGAATTGGTGAGTGGGT
R: ATAGCCCAAACCGTTGGT		 229–273 58 16 0.57 0.77 0.61 0.63
GB-AA-372 FJ647791 (TC)16 F: GGACTTCGGTCACCCTTC
R: CATCCAAAAACACCTCGG		 149–215 57 10 0.51 0.59 0.71 0.67
GB-AA-374 FJ647792 (CT)17 F: GAACGAATCAGGAATCGAAA
R: TGAAGTGTAATAAAAGACTTCGCA		 153–171 58 9 0.32 0.68 0.78 0.74
GB-AA-380 FJ647793 (CT)16 F: GGCAAACCTACACCCTCA
R: TTTTCTCGCTCCTCGTGA		 296–326 57 9 0.57 0.02 0.56 0.52
GB-AA-393 FJ647794 (GA)7 F: CAAGCAGTGAAGATGCTTACC
R: CAGCTCAGGGGTCGACTA		 118–216 57 20 0.22 0.68 0.87 0.88
GB-AA-398 FJ647795 (GA)11 F: CGGGAATGTGAAATCCTTT
R: CCAATTGCTTGGGAGTGA		 233–267 57 10 0.40 0.65 0.75 0.72
 Mean 10.3 0.39 0.55 0.72 0.69

*Loci with significant deviations from Hardy-Weinberg equilibrium.

Ta, annealing temperature; MAF, major allele frequency; A, number of alleles; He, expected heterozygosity; Ho, observed heterozygosity; PIC, polymorphism information content.

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Development of 34 New Microsatellite Markers from Actinidia arguta: Intra- and Interspecies Genetic Analysis
Plant Breed. Biotech.. 2013;1(2):137-147.   Published online June 30, 2013
DOI: https://doi.org/10.9787/PBB.2013.1.2.137
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Development of 34 New Microsatellite Markers from Actinidia arguta: Intra- and Interspecies Genetic Analysis
Plant Breed. Biotech.. 2013;1(2):137-147.   Published online June 30, 2013
DOI: https://doi.org/10.9787/PBB.2013.1.2.137
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Development of 34 New Microsatellite Markers from Actinidia arguta: Intra- and Interspecies Genetic Analysis
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Fig. 1 Phylogenetic dendrogram of the varieties and species in Actinidia based on SSR amplification profiles.

Fig. 1

Development of 34 New Microsatellite Markers from Actinidia arguta: Intra- and Interspecies Genetic Analysis

List of Actinidia species used in this study.

Taxon Number of accessions Variety Geographic location
A. arguta (Sieb. and Zucc.) Planch. ex Miq. var. arguta 40 63. K5-1-22 73. K5-3-6 83. K5-4-12 93. K5-10-1 Korea
64. K5-2-3 74. K5-3-7 84. K5-5-1 94. K5-10-2
65. K5-2-7 75. K5-3-8 85. K5-5-8 95. K5-10-3
66. K5-2-8 76. K5-3-12 86. K5-5-12 96. K5-10-5
67. K5-2-10 77. K5-3-13 87. K5-5-14 97. K5-10-8
68. K5-2-13 78. K5-3-18 88. K5-6-10 98. K5-11-1
69. K5-2-16 79. K5-4-3 89. K5-6-12 99. K5-11-2
70. K5-2-18 80. K5-4-7 90. K5-9-1 100. K5-11-3
71. K5-2-22 81. K5-4-8 91. K5-9-4 101. K5-11-8
72. K5-3-3 82. K5-4-10 92. K5-9-8 102. K5-12-6
A. chinensis Planch. var. chinensis 13 14. SKK3 20. SKK10 104. Red-Kiwi 106. Jesi-Gold Korea
16. SKK5 21. SKK11, 105. Hort16A
17. SKK7 (Gracies) 23. SKK13, 108. Yeo-San-Hyang
19. SKK9 (Chin Mei) 62. Jeju-Gold 115. Guem-Goi
A. chinensis Planch. var. chinensis 6 12. SKK1 30. S13 China
13. SKK2 15. SKK4 18. SKK8 (Tomuri) 117. SKK12-2
A. deliciosa (A. Chev.) C.F. Liang and A.R. Ferguson var. deliciosa 25 1. Abbott 7. Hyang-Rok 11. Yellow Queen (First Emperor) 45. SKK 60 New Zealand, Japan, China
2. Bruno 8. Golden King 38. SKK22 (Jinkui) 47. SKK80 (Red Princess)
3. Hayward 9. Golden Yellow 40. SKK33 (Wha-Pyung 2 Ho) 116. Jin-Mi
4. Monty 10. Sensation Apple 42. SKK43 (Seo-Hyang)
5. Matua 37. SKK18 (Chieftain) 43. SKK44 110. M51-2
6. Tomuri 39. SKK23 46. SKK 61
34. Sun-WuKong 41. SKK34 (Mi-Lyang 2 Ho) 109. M51-1
A. eriantha Benth. 3 50. S10 51. S20 103. Bi-Dan China, Korea
A. arguta var. purpurea (Rehd.) C.F. Liang 1 24. S3 China
A. kolomikta (Maxim. and Rupr.) Maxim. 1 25. S4 China
A. macrosperma C.F. Liang 1 27. S7 China
A. rufa (Sieb. and Zucc.) Planch. ex Miq. 1 61. Seom-Darae Korea

Efficiency of the procedure adopted for the identification of microsatellite markers in A. arguta.

Procedural step Number (percentage)
Sequenced clones 762
Redundant clones 35 (4.6%)
Unique clones 727 (95.4%)
SSR clones 565 (74.1%)
Truncated clones (5′ or 3′ end) 162 (21.3%)
Fewer than 12 nucleotides 263 (34.5%)
Primer pairs designed 140 (18.4%)
Polymorphic loci 34 (24.3%)z)

z)percentage based on the designed primer pairs.

Frequency and type of di-, tri- and ≥ tetra-nucleotide repeats isolated from the A. arguta microsatellite-enriched library.

Repeat unit Repeat class Number of microsatellite loci Polymorphic loci
Number Percentage Number Percentage
Di-nucleotide AC/CA/TG/GT 238 23.7% 8 17.4%
AG/GA/TC/CT 603 60.1% 30 65.2%
AT/TA 22 2.2%
CG/GC 1 0.1%
Total 864 86.1%
Tri-nucleotide AAC/ACA/CAA 15 1.5%
AAG/AGA/GAA 44 4.4% 1 2.2%
AAT/ATA/TAA 4 0.4%
ACC/CCA/CAC 3 0.3%
AGC/CGA/GAC 4 0.4%
AGG/GGA/GAG 14 1.4% 2 4.3%
ATC/TCA/CAT 1 0.1%
CCG/CGC/GCC 2 0.2%
Total 87 8.7%
≥ Tetra-nucleotide 53 5.8% 5 10.9%
Total repeat motifs 1004 46

Characteristics of 34 polymorphic microsatellite loci for Actinidia species.

Marker GeneBank accession Repeat motif Primer sequence Size (bp) Ta (°C) A MAF He Ho PIC
GB-AA-005 FJ647762 (CT)17 F: AGTTGTGCATCCAAAGGC
R: CAGTGGGGTGAAGAACGA		 192–218 57 12 0.32 0.73 0.78 0.76
GB-AA-012 FJ647763 (TG)13 F: TCACAACACTCATTTCGGC
R: ATCCGCTTCCTTAGCTGC		 154–176 58 10 0.49 0.47 0.71 0.68
GB-AA-015 FJ647764 (AG)19 F: CCTGGTCGTTCAGGGAAT
R: ATGGCATTTGTTGCCTTG		 267–293 58 14 0.24 0.89 0.83 0.83
GB-AA-017 FJ647765 (CT)6 F: AAAGTGTGAGCACGTGACAA
R: TGAGAGAGAGAGGTGGCG		 170–182 58 2 0.54 0.00 0.50 0.37
GB-AA-018 FJ647766 (CA)8, (GGA)4 F: ACCATGGCACAGATGGAA
R: TCCAGTGCCTTTTTAAGCC		 147–171 58 11 0.23 0.75 0.81 0.80
GB-AA-024 FJ647767 (GA)19 F: AGGAGACCCAACAGGAACA
R: AATTCGGGTCACCACACA		 155–181 58 12 0.40 0.49 0.75 0.74
GB-AA-054 FJ647768 (GA)15 F: ACCAAAAACCACCTGCCT
R: TGAACCCGTATTCGCATC		 186–214 58 15 0.23 0.87 0.85 0.84
GB-AA-065 FJ647769 (GA)11(GAA)23 F: ATTGAAGCCCCCATTGAG
R: CCAAGGAGGGCATTTAGG		 212–238 58 11 0.43 0.60 0.74 0.72
GB-AA-069 FJ647770 (GGGA)6(GA)8 F: CGTTCTCCTTCGACCCTT
R: CCGTTACCTTGTCCAATCC		 196–258 58 11 0.43 0.67 0.74 0.71
GB-AA-080 FJ647771 (GA)15 F: CCAATCAACAAGATGCACG
R: TGGGAGGTTGAAACTGGA		 179–213 58 11 0.26 1.00 0.82 0.80
GB-AA-084 FJ647772 (GA)15 F: CATTCGAACCAACGCAAT
R: AGTCGGAGCTGGGAGAAG		 233–259 58 12 0.22 0.96 0.83 0.82
GB-AA-088 FJ647773 (CT)7 F: TCTGGTTTGTTTTCCACCA
R: GGTTGAGTTCCATTCCCG		 177–197 57 8 0.45 0.56 0.69 0.67
GB-AA-091 FJ647774 (CT)19 F: TGACTTAAGGGCGACCAA
R: GGAAATCGCTCATGGACA		 201–223 58 8 0.38 0.62 0.74 0.69
GB-AA-094 FJ647775 (AC)15 F: ACAGGGGAACATCAGTGC
R: GTGGGATATAACCGGGGA		 208–220 57 6 0.38 0.41 0.68 0.63
GB-AA-096 FJ647776 (GA)6, (GA)3 F: TTGGTACACAAGACGCCC
R: GAAATTTCTTCACCCGCC		 229–235 58 3 0.52 0.01 0.50 0.39
GB-AA-302 FJ647777 (AG)13 F: TCGGTGATAAATGGCAGG
R: GGCTCCTTGACAGCACAG		 269–311 58 11 0.43 0.31 0.74 0.72
GB-AA-303 FJ647778 (CT)15 F: TGGGGCATTTATGCCTAT
R: TCCAACCTTCTTGGCTCA		 156–258 57 12 0.33 0.35 0.75 0.73
GB-AA-304 FJ647779 (AG)11 F: CAGTCCACAAAATGGGTCA
R: GGTGAACACCCCCAAAGT		 202–364 58 13 0.41 0.15 0.67 0.64
GB-AA-308 FJ647780 (CCCT)4, (GGGT)2, (GGGT)2 F:TAGTGCTGCGAAGGAGGA
R: ATTGCACCATTCTGTGGC		 265–304 58 8 0.32 0.36 0.77 0.75
GB-AA-331 FJ647781 (GA)15, (CAGA)4 F: CCATCTTTTTGTGCCTTTG
R: TTGTTGGTATCATGCCCC		 259–303 57 13 0.28 0.59 0.83 0.80
GB-AA-333 FJ647782 (TG)12 F: AAGTTCATTCCACGCACG
R: ATTGCATTTGAGCCGCTA		 242–276 58 6 0.49 1.00 0.67 0.61
GB-AA-337 FJ647783 (GA)10, (AC)6 F: TTCTCTGCGCGTTCTCTC
R: AGCCTCAACCAAGAAGGG		 290–332 58 10 0.36 0.53 0.74 0.72
GB-AA-340 FJ647784 (CCT)5 F: AAGGAATTCGCCCTCAAA
R: GGCTGACAAGAAGCGATG		 287–296 58 4 0.65 0.68 0.49 0.45
GB-AA-342 FJ647785 (GA)2, (GA)4 F: AAAATTCCAATTCCCCCA
R: CATTTCGGAATCCCCTTT		 261–293 57 13 0.35 0.59 0.81 0.80
GB-AA-343 FJ647786 (AG)14 F: TGCTTCTTCGGTCATGCT
R: CACCATTTCGAACCCAGA		 232–262 58 5 0.44 0.67 0.70 0.64
GB-AA-356 FJ647787 (AC)12 F: CCCGACTTCCAAGTCTCC
R: CTCCGGATGCCCTTTATC		 251–287 58 16 0.25 0.70 0.85 0.83
GB-AA-366 FJ647788 (GA)7 F: CAGCTCCAAGGGCTATGA
R: TGTTCCCACTACCGCAAC		 241–247 57 5 0.51 0.09 0.53 0.43
GB-AA-369 FJ647789 (CT)16(CA)17 F: TGATCCACAACGTCATCAA
R: GGGCACGCTAGACACACC		 185–215 58 13 0.32 0.31 0.76 0.74
GB-AA-370 FJ647790 (GA)16 F: GGGAATTGGTGAGTGGGT
R: ATAGCCCAAACCGTTGGT		 229–273 58 16 0.57 0.77 0.61 0.63
GB-AA-372 FJ647791 (TC)16 F: GGACTTCGGTCACCCTTC
R: CATCCAAAAACACCTCGG		 149–215 57 10 0.51 0.59 0.71 0.67
GB-AA-374 FJ647792 (CT)17 F: GAACGAATCAGGAATCGAAA
R: TGAAGTGTAATAAAAGACTTCGCA		 153–171 58 9 0.32 0.68 0.78 0.74
GB-AA-380 FJ647793 (CT)16 F: GGCAAACCTACACCCTCA
R: TTTTCTCGCTCCTCGTGA		 296–326 57 9 0.57 0.02 0.56 0.52
GB-AA-393 FJ647794 (GA)7 F: CAAGCAGTGAAGATGCTTACC
R: CAGCTCAGGGGTCGACTA		 118–216 57 20 0.22 0.68 0.87 0.88
GB-AA-398 FJ647795 (GA)11 F: CGGGAATGTGAAATCCTTT
R: CCAATTGCTTGGGAGTGA		 233–267 57 10 0.40 0.65 0.75 0.72
 Mean 10.3 0.39 0.55 0.72 0.69

*Loci with significant deviations from Hardy-Weinberg equilibrium.

Ta, annealing temperature; MAF, major allele frequency; A, number of alleles; He, expected heterozygosity; Ho, observed heterozygosity; PIC, polymorphism information content.

Table 1 List of Actinidia species used in this study.
Table 2 Efficiency of the procedure adopted for the identification of microsatellite markers in A. arguta.

percentage based on the designed primer pairs.

Table 3 Frequency and type of di-, tri- and ≥ tetra-nucleotide repeats isolated from the A. arguta microsatellite-enriched library.
Table 4 Characteristics of 34 polymorphic microsatellite loci for Actinidia species.

Loci with significant deviations from Hardy-Weinberg equilibrium.

Ta, annealing temperature; MAF, major allele frequency; A, number of alleles; He, expected heterozygosity; Ho, observed heterozygosity; PIC, polymorphism information content.

Table 1

Table 2

Table 3

Table 4

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