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Brief Report

Genetic Diversity of 52 Species of Kiwifruit (Actinidia chinensis Planch.)

Guangxi Key Laboratory of Plant Functional Phytochemicals and Sustainable Utilization, Guangxi Institute of Botany, Guangxi Zhuang Autonomous Region and Chinese Academy of Sciences, Guilin 541006, China
*
Authors to whom correspondence should be addressed.
Horticulturae 2023, 9(7), 753; https://doi.org/10.3390/horticulturae9070753
Submission received: 6 April 2023 / Revised: 5 June 2023 / Accepted: 14 June 2023 / Published: 28 June 2023
(This article belongs to the Section Genetics, Genomics, Breeding, and Biotechnology (G2B2))

Abstract

:
The genetic diversity of 52 kiwifruit wild germplasms, which were collected by the kiwifruit germplasm nursery of the Guangxi Institute of Botany, was studied using start-codon-targeted (SCoT) molecular markers. The objective was to understand the genetic relationships of the 52 kiwifruit wild germplasms. The results showed that a total of 113 bands were amplified from 52 wild kiwifruit germplasms using 10 primers (9–17 bands per primer, 11.3 on average), of which 103 (91.15%) were polymorphic bands (10.3 bands per primer). The genetic identity of the 52 wild kiwifruit germplasms was in the range of 0.405–1.000, with an average of 0.709. The genetic distance was 0.000–0.904, with an average of 0.355. At the threshold of 0.650, the germplasms were clustered into three clusters. The genetic distances between Guilin and Fushekuoye and between Jinhua and Liangye were both the smallest (0.000), meaning they had a similarity of 100%, as indicated by the SCoT molecular markers. In conclusion, the genetic relationships at the molecular level (genetic distance) were clustered preferentially according to the place of origin instead of by morphological classification, geographical distribution, or ploidy. The genetic relationships between wild kiwifruit germplasms were partially verified through disease resistance analysis.

1. Introduction

Kiwifruit (Actinidia chinensis Planch.) is a perennial dioecious deciduous vine plant belonging to the Actinidia Lindl. genus of the Actinidiaceae family. According to the newest classification system, kiwifruit is classified into 75 taxa that include 54 species and 21 subspecies [1]. The A. chinensis Planch. and A. chinensis var. deliciosa are categorized as two subspecies under A. chinensis. China is the center of Actinidia plant distribution and is rich in wild germplasms [2]. Since 1978, when the study and industrial development of Chinese kiwifruit began, the domestication from wild kiwifruit to A. chinensis Planch and A. chinensis var. deliciosa and the orchard cultivation of their large-sized varieties have been ongoing [3,4]. These efforts have realized the industrialization of kiwifruit production while altering the world’s kiwifruit production pattern, which has been mainly dominated by Hayward, a New Zealand kiwifruit variety [5,6]. In the early years of China’s kiwifruit industrialization, some Chinese researchers conducted surveys, collections, and preservation of wild resources [7]. In recent years, the innovative use of germplasm resources has mostly focused on the selection of wild resources, seedling breeding, and intraspecific and intraspecific hybridization breeding [8], of which crossbreeding has become the mainstream method of kiwifruit improvement [9,10]. With the deepening genetic research into natural kiwifruit populations, understanding the genetic relationships between wild kiwifruit resources and breeding and improving existing wild species through distant hybridization have become important parts of the innovative utilization of kiwifruit germplasm resources [11].
Start-codon-targeted (SCoT) polymorphic markers are new molecular markers for new target genes based on sequence-related amplified polymorphism (SRAP) [12]. SCoT molecular markers have the advantages of both inter simple sequence repeat and random amplified polymorphic DNA (RAPD) markers and are characterized by simple procedures [13], low cost, high amplification efficiency, good repeatability, and large amount of genetic information [14]. Therefore, SCoT molecular markers have been widely used in the analysis of genetic diversity and the relationships between germplasm resources, germplasm identification, and construction of genetic maps [15,16,17]. They are expected to show promise in variety identification and evolutionary analyses [13].
Previously, Wang et al. [18] analyzed 64 grape germplasm resources using SCoT markers, and the clustering results showed that wild grape germplasm resources originating in China and the United States can be completely separated. Guo et al. [19] applied SCoT markers to 22 wild grape varieties and 24 “bull heart” grape germplasms, demonstrating that SCoT markers can effectively reveal the genetic diversity of these germplasms and reflect the geography of their origins to a degree, indicating that geographical factors could have a great influence on the genetic relationships between persimmon germplasms [20]. Chen et al. (2010) investigated 24 longan germplasms using SCoT markers, finding that SCoT markers can reveal high genetic diversity in the longan germplasms, and concluded that the genetic relationships of longan were highly correlated with geographical factors [21]. In 1976, the Guangxi Institute of Botany started the taxonomic study of kiwifruit along with surveying, collecting, and preserving wild germplasm resources. At present, the Guangxi Institute of Botany’s large-scale kiwifruit germplasm nursery [22] includes more than 40 items, with over 60 domestic and foreign cultivated varieties (lines), providing a rich material basis for genetic diversity analysis.
In the present study, a genetic diversity analysis was conducted on 52 wild kiwifruit germplasms collected in the Germplasm Nursery of the Guangxi Institute of Botany using SCoT molecular markers to provide data support for transcriptome analysis of wild kiwifruit germplasm and crossbreeding, so that many kiwifruit resources with desirable traits and good development potential can be utilized. By providing new evidence from the perspective of genetics in combination with morphology, this study can serve as a reference for the classification of kiwifruit, an effort that is currently under debate.

2. Materials and Methods

2.1. Materials

Fifty-two wild kiwifruit germplasms were provided by the Kiwifruit Germplasm Nursery of the Guangxi Institute of Botany (Table 1). Young leaves were collected from 1-year-old seedlings and dried and preserved in a desiccator for SCot analysis.

2.2. Methods

2.2.1. DNA Extraction, Detection, and Quantitative Dilution

Genomic DNA was extracted from each of 52 kiwifruit germplasms using a plant genomic DNA extraction kit (Vazyme Biotech, Nanjing, China). Its quality was assessed through agarose gel electrophoresis, and its concentration was determined through UV spectrophotometry. All qualified genomic DNAs were diluted to a final concentration of 50 ng·μL−1 with 1× Tris hydrochloride buffer (pH = 8.0) and stored in a −20 °C freezer.

2.2.2. Primer Screening

The SCoT primers used in this study were prepared based on the 36 primer sequences of Collard and Mackill [23] and then screened on the Bio-Rad S1000 thermal cycler, from which 10 SCoT primers that yielded clearly separated bands and rich polymorphism were selected to be used for amplification of all DNA samples (Table 2).

2.2.3. PCR and Detection

The 20-μL reaction system for SCoT primer amplification was as follows: 10 μL of 2× Taq PCR Mix, 1.0 μL of DNA template (50 ng·μL−1), 0.6 μL of each primer (10 μmol·L−1), and 8.4 μL of ultrapure water. The cycling was as follows: initial denaturation at 94 °C for 5 min, 35 cycles of denaturation at 94 °C for 1 min, annealing at 50 °C for 1 min, extension at 72 °C for 2 min, and final extension at 72 °C for 8 min. After the amplification, 8 μL of amplification product was subject to gel electrophoresis (2% agarose gel) and visualized and photographed through a gel imaging system.

2.2.4. Data Analysis

The presence or absence of bands at a certain position on the agarose gel for each of the SCoT primers was manually counted (presence = 1; absence = 0). PCR amplification was done twice for each SCoT primer, and only the bands that showed up in both reactions were counted. The counting was performed separately by two individuals to reduce human error. The data were entered into an Excel spreadsheet, based on which a 0/1 matrix database of SCoT amplification profiles was established. The genetic identity and genetic distance between samples were calculated using the genetic distance tool of numerical taxonomy and multivariate analysis system (NTSYSpc, version 2.10e, Exeter Software, New York, USA). Cluster analysis was performed using the unweighted pair group method with arithmetic mean (UPGMA) through the SAHN clustering technique. Clustering graphs were generated using the Tree plot tool of NTSYSpc.

3. Results

3.1. Genomic DNA Extraction

The electrophoresis results of 52 genomic DNA extractions of wild kiwifruit germplasms are shown in Figure 1, indicating the genomic DNA preparations were of high quality and integrity, with distinctive bands and no streaks or degradation. The concentration and purity were measured by spectrophotometer and met the requirements of subsequent tests.

3.2. Analysis of the Polymorphism of Bands

A total of 113 bands were amplified from 52 wild kiwifruit germplasms using 10 primers (9–17 bands per primer, 11.3 on average). Of them, 103 (91.15%) were polymorphic bands. The size of the bands was in the range of 750–2000 bp, which we used in the analysis of the relationships between samples. The PCR results of some primers are listed in Figure 1.

3.3. Genetic Identity, Genetic Distance, and Cluster Analysis

According to the amplification results, the genetic identity and genetic distance between 52 wild kiwifruit germplasms were analyzed with NTSYSpc. The results showed that the genetic identity of the 52 wild kiwifruit germplasm resources was in the range of 0.405–0.976, with an average of 0.691; the genetic distance was 0.024–0.904, with an average value of 0.44. The genetic identity of the 18 wild species from Guangxi was 0.452–0.976, with an average of 0.714; the genetic distance was 0.100–0.793, with an average of 0.447. The genetic identity of wild species from the other eight regions was 0.405–0.952, with an average of 0.679; the genetic distance was 0.049–0.904, with an average of 0.477. The genetic identity of the 23 wild kiwifruit germplasms (polyploidy: 2×) was 0.405–0.976, with an average of 0.691; the genetic distance was 0.024–0.904, with an average of 0.464.
Based on the above genetic distances, the dendrogram of all 52 wild kiwifruit germplasms was constructed using the UPGMA method. With a threshold 0.650, the germplasms could be clustered into three classes (Figure 2). The first class included 48 kiwifruit germplasms. The second class included only A. macrosperma C.F.Liang. The third class included A. jiangxiensis C.F.Liang, A. melliana Hand.-Mazz, and Hongsi. Two groups of germplasms, namely, those between Ziguo and Ziguo ♂, and between Jinhua and Liangye, showed the smallest genetic distance (0.024), meaning they had a similarity of 97.6%, as indicated by SCoT molecular markers. The genetic distance between Hongsi and Jingli was the largest, at 0.904, with a similarity of 40.5%, as indicated by SCoT molecular markers. A. macrosperma C.F.Liang, as a germplasm with distinct characteristics, was clustered into its own class.
Considering all 52 wild kiwifruit germplasms in this study, their genetic relationships at the molecular level (genetic distance) were clustered preferentially according to the place of origin instead of the morphological classification, geographical distribution, or ploidy. For example, in terms of the place of origin, Maohua and Anxixiang (with places of origin in Fujian and Guangdong, respectively, and a genetic distance of 0.241) were closely clustered separately from the others, as were Jinhua, Zhuguo, and Honghualaingguang (with a places of origin in Guangxi and Guizhou, respectively, and a genetic distance of 0.182–0.405) and Lijiang and Maoyeyingchi (with a place of origin in the Yangtze River Basin and a genetic distance of 0.304). This phenomenon indicates that wild kiwifruit germplasms from the same place of origin have low genetic diversity between themselves, while those from different geographic regions have high genetic diversity.

3.4. Population Structure Analysis and Principal Coordinate Analysis

The population structure analysis divided 52 germplasms into 3 groups (Figure 3), of which group I included 16 germplasms (30.77%), such as Actinidia carnosifolia var. Glaucescens ♂, A. pentapetala, A. guilinensis, etc.; group II included 22 germplasms (42.31%), including A. latifolia (Fushekuoye), Actinidia callosa var. henryi Maxim, A. guilinensis, etc.; and group III included 14 germplasms (26.92%), such as A. arguta var. purpurea (Rehd.) C.F.Liang ♂, A. tetramera, and A. glaucophylla, etc. Generally, the accessions from different sources were distributed into every group, and there was no clear correlation with the geographical location.
Principal coordinate analysis revealed that the contributions rates of the first three principal coordinates are 47.18%, 34.44%, and 19.87%, respectively. The results of principal coordinate analysis were in accordance with the results of cluster analysis and genetic structure analysis. The 52 germplasms evaluated in the present study were divided into 3 groups: in particular, A. macrosperma C.F.Liang was divided into its own category, and the relationships between A. chrysantha C.F.Liang and A. callosa Lindl were more closed. Principal coordinate analysis provided a more intuitive display of the phylogenetic relationships of the germplasms and indicated that frequent gene exchange existed in the genus Actinidia (Figure 4).

4. Discussion

The level of genetic diversity determines the adaptability of a species to the environment and its evolutionary potential, and the latter two are positively correlated. The basis for the utilization of germplasm resources is a comprehensive understanding of their genetic diversity, and molecular-biological methods provide an effective way to utilize genetic diversity. In this study, a total of 113 bands were amplified from 52 wild kiwifruit germplasms using 10 primers (9–17 bands per primer, 11.3 on average), of which 103 (91.15%) were polymorphic bands. The genetic identity was in the range of 0.405–0.976, with an average of 0.691, and the genetic distance was 0.024–0.904, with an average of 0.464, indicating that these germplasms are rich in genetic diversity. Three groups were closely clustered separately from the others: Maohua and Anxixiang (with places of origin in Fujian and Guangdong respectively); Jinhua, Zhuguo, and Honghualaingguang (with places of origin in Guangxi and Guizhou respectively); and Lijiang and Maoyeyingchi (with a place of origin in the Yangtze River Basin). These findings are consistent with the kiwifruit groups divided according geographic region, such as northern China, the Yangtze River basin, southern China, southeastern China, and southwestern China [24,25,26,27,28]. Male and female plants of the same species and intraspecific subspecies often closely cluster, with high genetic similarity [28]. For example, both the Ziguo, Ziguo ♂, (0.429) and the Maohua and Zongmaomaohua pair (0.241) had small genetic distances.
However, the subspecies did not cluster preferentially according to the genetic similarity [28]. For example, Jingli, Maoyeyingchi, and Yise are all subspecies of Yingchi but did not have small genetic distances. Wangmai is a transition type of the Banguo group, and the morphological differences between Guilin and Kuoye are large enough to differentiate the two. In this study, Guilin and Kuoye were clustered into the same class (Kuoye) [29] and had a small genetic distance from each other. Lingui and Wantian were in the same cluster and might be members of different populations of the same species, given that they are from the same source. Fushekuoye, Yuanguokuoye, Kuoye, and Anxixiang are closely related [27,30,31], which was confirmed in this study by the genetic distances of 0.182, 0.182, and 0.127, meaning they were tightly clustered. No germplasms were found to be closely related to A. macrosperma C.F.Liang [31]. Molecular genetic evidence [27] supports that A. macrosperma C.F.Liang and Dui’e could be closely related in maternal lineage (0.442), which was also verified in the present study. Luanyuanye, Rongshui, Taohua, Lijiang, and Lingui are native to Guangxi and were clustered within a small genetic distance of 0.127–0.442. Three Maohua germplasms, i.e., Mianmao, Hongsi, and Ersehua, were not in the same cluster, and they had a genetic distance of 0.519–0.560, likely due to the limitations of SCoT markers caused by insufficient primers. Polymorphic sites in the genomes of polyploid plants are more complex and have a higher degree of variation, so this phenomenon can easily occur when the marker primers used or the polymorphic sites produced are too few. In the present study, the 52 germplasms were divided into 3 groups by cluster analysis (Figure 2), which is supported by the results of population structure analysis (Figure 3) and principal coordinate analysis (Figure 4). Additionally, the results of principal coordinate analysis provide a more intuitive indication that frequent gene exchange exists in the genus Actinidia.
The morphological classification of kiwifruit has been controversial, without a stringent standard. In addition, the ex situ conservation of samples, differences in traits between the plant in the wild and under nursery cultivation, and incomplete records about the origins of the samples collected in the last century further complicate the classification. The materials used in this study have been collected from all over the country since 1980 and are currently preserved in the germplasm nursery of the Guangxi Institute of Botany. Our clustering results were slightly different from those of previous studies based on geographical region. In this study, A. macrosperma C.F.Liang was not particularly closely related to any species and clustered into its own class, which is in contradiction to the previous finding that A. macrosperma C.F.Liang and Anxixiang had the smallest genetic distance [32], a discrepancy that is likely due to the differences in methods of collecting experimental materials and the unreliability of records on origins. The clustering results obtained with limited numbers of samples or relatively concentrated sampling often do not match those obtained after expanding the sampling scope and increasing the number of samples, since the increased number of samples may dilute the calculated genetic relationships, thereby distorting the genetic distance between each two or more germplasms.
The results obtained using different markers also differ. A restriction fragment length polymorphism (RFLP) analysis of the chloroplast DNA of kiwifruits from four regions showed that A. kolomikta was vastly different from the kiwifruit species in the Jingguo group [33]. In contrast, the RAPD analysis supported that A. kolomikta should be classified into the Jingguo group [27,34]. Due to the presence of transitional types and differences in type specimens between different periods, the same species can have different names, which also caused some inconsistent results in this study. For example, Yise, which is a subspecies of Yingchi, is actually the Fanjingshan kiwifruit. Therefore, to clarify the relationships within the genus Actinidia and settle the classification dispute, it is necessary to undertake a complicated process in which the evidence obtained through various comprehensive methods would be collated and summarized.
Previously, the canker disease resistance of 42 materials used in this study was evaluated through artificial inoculation [18], based on which the materials were categorized into four groups, i.e., HR, T, S, and HS (Figure 5). The comparison of the resistance-based grouping results with the clustering results found that in a small range, materials with the same resistance preferentially clustered in the same class. For example, materials with the resistance of T, e.g., Jingli, Ersehua, Guilin, Yuanguokuoye, Kuoye, Wangmaibianyi, Zongmaomaohua, and Anxixiang, were clustered in the first class. Materials with the resistance of HS or S, e.g., Luanyuanye, Maoyeyingchi, Wantian, Rongshui, and Lijiang, showed a small genetic distance from each other, and Wantian, Rongshui, and Lijiang exhibited the phenomenon that the materials from the same place of origin tended to cluster together since they are endemic to Guangxi. Materials with the resistance of HR, e.g., Ziguo, Si’e, Ruanzao, Dui’e, Zhejiangmaohua, and Gezao, also showed a small genetic distance from each other. Their disease resistance also provides new evidence supporting the notion that A. macrosperma C.F.Liang and Dui’e are closely related in maternal lineage [27,30,35].

5. Conclusions

In this study, the genetic diversity of 52 wild kiwifruit germplasms collected in the Germplasm Nursery of Guangxi Institute of Botany were analyzed using SCoT molecular markers. A total of 113 bands were amplified from 52 wild kiwifruit germplasms using 10 primers (9–17 bands per primer, 11.3 on average). Of the bands, 103 (91.15%) were polymorphic. The genetic distances of the 52 wild germplasm resources were in the range of 0.000–0.976. The clustering results showed that the genetic relationships of wild resources had a tendency to cluster according to the place of origin.

Author Contributions

Conceptualization, B.Q. and J.L.; methodology, B.Q. and F.W.; software, B.Q.; validation, B.Q., F.W. and J.L.; investigation, B.Q.; resources, J.L., K.Y., Q.M. and Q.J.; data curation, B.Q.; writing—original draft preparation, B.Q.; writing—review and editing, B.Q., F.W., K.Y. and J.L.; supervision, Q.M., H.G., P.L., Q.J. and J.L.; project administration, B.Q., F.W. and J.L.; funding acquisition, B.Q., F.W. and J.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (grant no. 32260733), the Guangxi Natural Science Foundation (grants no. 2020GXNSFBA297046), the Project for Fundamental Research of the Guangxi Institute of Botany (grants no. 21008), the Innovation-Driven Special Foundation of Guangxi (grants no. AA23023008), and the Guilin Innovation Platform and Talent Plan (grant no. 20210102-3).

Data Availability Statement

All data are available in the manuscript.

Acknowledgments

The authors thank the anonymous reviewers for their work.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Amplification profile of SCoT prime of species (genotype) No. 1–48, which are presented in Table 1. M is DL250 DNA marker.
Figure 1. Amplification profile of SCoT prime of species (genotype) No. 1–48, which are presented in Table 1. M is DL250 DNA marker.
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Figure 2. Dendrogram of 52 wild germplasms of kiwifruit (Actinidia chinensis Planch.) by 10 SCoT primes.
Figure 2. Dendrogram of 52 wild germplasms of kiwifruit (Actinidia chinensis Planch.) by 10 SCoT primes.
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Figure 3. Population structure analysis of 52 wild germplasms of kiwifruit (Actinidia chinensis Planch.) by 10 SCoT primes.
Figure 3. Population structure analysis of 52 wild germplasms of kiwifruit (Actinidia chinensis Planch.) by 10 SCoT primes.
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Figure 4. Principal coordinates of 52 wild germplasms of kiwifruit (Actinidia chinensis Planch.) by 10 SCoT primes.
Figure 4. Principal coordinates of 52 wild germplasms of kiwifruit (Actinidia chinensis Planch.) by 10 SCoT primes.
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Figure 5. Part of wild germplasms of kiwifruit resistance of Pseudomonas syringae pv. actinidiae. Note: (A) symptoms of germplasms highly resistant to Pseudomonas syringae pv. actinidiae (HR); (B) symptoms of germplasms susceptible to Pseudomonas syringae pv. actinidiae (S); (C) symptoms of germplasms highly susceptible to Pseudomonas syringae pv. actinidiae (HS); (D) symptoms of germplasms moderate resistant to Pseudomonas syringae pv. actinidiae (T). Symptoms of lesions on canes of representative genotypes of different actinidia species induced by inoculation of Pseudomonas syringae pv. actinidiae and kiwifruit resistance of Pseudomonas syringae pv. actinidiae are referred to in our previous studies [18,36].
Figure 5. Part of wild germplasms of kiwifruit resistance of Pseudomonas syringae pv. actinidiae. Note: (A) symptoms of germplasms highly resistant to Pseudomonas syringae pv. actinidiae (HR); (B) symptoms of germplasms susceptible to Pseudomonas syringae pv. actinidiae (S); (C) symptoms of germplasms highly susceptible to Pseudomonas syringae pv. actinidiae (HS); (D) symptoms of germplasms moderate resistant to Pseudomonas syringae pv. actinidiae (T). Symptoms of lesions on canes of representative genotypes of different actinidia species induced by inoculation of Pseudomonas syringae pv. actinidiae and kiwifruit resistance of Pseudomonas syringae pv. actinidiae are referred to in our previous studies [18,36].
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Table 1. Fifty-two kiwifruit germplasm resources used in this study.
Table 1. Fifty-two kiwifruit germplasm resources used in this study.
No.Species (Genotype)Distribution/
Origin
PloidyResponse to pseudomonas syringae pv. actinidia
1A. callosa var. henryi Maxim.Guangxi, China2x 4xT
2A.diversicoloraSichuan, China2xT
3A. jiangxiensis C.F.LiangJiangxi, China2xT
4A.arguta var. purpurea (Rehd.) C.F.LiangGuangxi, China4x 8xHR
5A. pentapetalaGuangxi, China2xS
6A.macrosperma C.F.LiangZhejiang, China4xHR
7A. guilinensisGuangxi, China2xT
8A. latifolia (Fushekuoye)Shanxi, China2x
9A. latifolia (Yuanguokuoye)Hubei, China T
10A.carnosifolia var. glaucescensGuangxi, China
11A. Eriantha (Baihuamaohua)Wuhan, China2xS
12A. Latifolia (Tuomaokuoye)Sichuan, China2xS
13A.arguta (Sieb.et Zucc.) Planch.et Miq.Heilongjiang, China4xHR
14A. hemsleyana DunnGuangxi, China2x
15A. cylindrica var. reticulataGuangxi, China2x T
16A. tetrameraGuangdong, China4xHR
17A. Eriantha (Zhejiang Maohua)Jiangxi, China2xHR
18A.valvata DunnHunan, China4xHR
19A. cylindricaGuangxi, China2xS
20A. eriantha (GDC Maohua)Wuhan, China2x
21A.polygamya (Sieb.et Zucc.) Maxim.Yunnan, China4x HR
22A. indochinensis var. ovatifoliaGuangxi, China2xHS
23A. melliana Hand.-Mazz.Guangxi, China2xHS
24A. persicinaGuangxi, China2xT
25A. callosa var. strigosaGuangxi, China4xHS
26A. latifolia (Gardn.et Champ.) Merr.Guangxi, China2xT
27A. longicarpaSichuan, China2xT
28A. latifolia (Tuguokuoye)Guangxi, China2xT
29A. rongshuiensisGuangxi, China2xS
30A. callosa var. strigosaWuhan, China4xHS
31A. erianthaGuangxi, China2xHR
32A.arguta var. purpurea (Rehd.) C.F.Liang ♂Jiangxi, China4x 8xHR
33A. wantianensisGuangxi, China2xS
34A. eriantha (Duanguomaohua)Guangxi, China2x
35A. fulvicoma var. lanata (Hemsl.)
C.F.Liang
Hunan, China2x
36A. guilinensisGuangxi, China2xT
37A. callosa var. discolor C.F.LiangGuangxi, China2x 4xT
38A. chrysantha C.F.LiangGuangxi, China4xT
39A. rubricaulis var. coriaceaSichuan, China2xS
40A. callosa Lindl2xS
41A. rubricaulis var. coriacea (Finet Gagn) C.F.LiangGuangxi, China2xS
42A. glaucophyllaGuangxi, China2xHS
43A.liangguangensis var. rubrifloraGuangxi, China2xT
44A. cylindricaGuangxi, China2xS
45A. eriantha var. bruneaGuangxi, China2xT
46A. cylindrica var. reticulataGuangxi, China2x 4xT
47A.chinensis Planch × A.eriantha BenthGuangxi, China
48A. arguta (Hongrouruanzao)Guangxi, China
49ZY-2Guangxi, China4xT
50A. albicalyxGuangxi, China2xT
51A. styracifolia C.F.LiangFujian, China2xT
52A. lijiangensisGuangxi, China2xS
Note: HR, highly resistant to Pseudomonas syringae pv. actinidiae; S, susceptible to Pseudomonas syringae pv. actinidiae; HS, highly susceptible to Pseudomonas syringae pv. actinidiae; T, moderately resistant to Pseudomonas syringae pv. actinidiae.
Table 2. Sequences and amplification efficiency of SCoT primers.
Table 2. Sequences and amplification efficiency of SCoT primers.
SCoT PrimersSequence (5′-3′)Total BandsPolymorphic BandsPercentage of Polymorphic Bands (%)
P1CAACAATGGCTACCACCA99100.0
P3CAACAATGGCTACCACCG111090.9
P4CAACAATGGCTACCACCT10880.0
P8CAACAATGGCTACCACGT9888.8
P11AAGCAATGGCTACCACCA1111100.0
P12ACGACATGGCGACCAACG151493.3
P13ACGACATGGCGACCATCG111090.9
P36GCAACAATGGCTACCACC99100
P37ACGACATGGCGACCAGCG171588.2
P38ACGACATGGCGACCACCG11981.8
Total113103
Average11.310.391.15
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MDPI and ACS Style

Qi, B.; Wang, F.; Ye, K.; Mo, Q.; Gong, H.; Liu, P.; Jiang, Q.; Li, J. Genetic Diversity of 52 Species of Kiwifruit (Actinidia chinensis Planch.). Horticulturae 2023, 9, 753. https://doi.org/10.3390/horticulturae9070753

AMA Style

Qi B, Wang F, Ye K, Mo Q, Gong H, Liu P, Jiang Q, Li J. Genetic Diversity of 52 Species of Kiwifruit (Actinidia chinensis Planch.). Horticulturae. 2023; 9(7):753. https://doi.org/10.3390/horticulturae9070753

Chicago/Turabian Style

Qi, Beibei, Faming Wang, Kaiyu Ye, Quanhui Mo, Hongjuan Gong, Pingping Liu, Qiaosheng Jiang, and Jiewei Li. 2023. "Genetic Diversity of 52 Species of Kiwifruit (Actinidia chinensis Planch.)" Horticulturae 9, no. 7: 753. https://doi.org/10.3390/horticulturae9070753

APA Style

Qi, B., Wang, F., Ye, K., Mo, Q., Gong, H., Liu, P., Jiang, Q., & Li, J. (2023). Genetic Diversity of 52 Species of Kiwifruit (Actinidia chinensis Planch.). Horticulturae, 9(7), 753. https://doi.org/10.3390/horticulturae9070753

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