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Article

Genetic Analysis of the Cultivars of Ping’ou Hybrid Hazelnut (C. heterophylla Fisch. × C. avellana L.) in China Based on SSR Markers

by
Zhen Yang
1,
Tiantian Zhao
1,
Lisong Liang
1,
Lei Jiang
2,
Lujun Wang
3,
Sihao Hou
1 and
Qinghua Ma
1,*
1
Key Laboratory of Tree Breeding and Cultivation of the National Forestry and Grassland Administration/Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
2
Langfang Academy of Agricultural and Forestry Sciences, Langfang 065000, China
3
Anhui Academy of Forestry, Hefei 230031, China
*
Author to whom correspondence should be addressed.
Forests 2023, 14(7), 1405; https://doi.org/10.3390/f14071405
Submission received: 27 May 2023 / Revised: 29 June 2023 / Accepted: 5 July 2023 / Published: 10 July 2023
(This article belongs to the Special Issue Advances in Hazelnut Germplasm and Genetic Improvement)
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Abstract

:
Ping’ou hybrid hazelnut is one of the most profitable tree nuts in China, but economically important cultivars must first be genetically validated to meet industrial demand. Traditional approaches used for cultivar identification are mainly trait-based and unreliable. Previous approaches at the DNA level, focusing on the identification of species or/and varieties that originated in China, were not used widely in hybrid hazelnut because there was no proper standard sample. In this research, a multiplexed fingerprinting test was conducted to allow for hazelnut cultivar identification using SSR markers derived from European hazelnut. Twenty-seven SSR markers were used to fingerprint 57 genetically unique Ping’ou hybrid hazelnut and related wild species. All markers showed a high level of polymorphism, as indicated by mean values for observed heterozygosity (Ho = 0.84), expected heterozygosity (He = 0.80), and polymorphism information content (PIC = 0.78). A total of 301 alleles were detected, and the number of effective alleles varied from 6 for KG817 and GB818 to 18 for B654, with an average of 11.2 alleles per locus. Moreover, the Shannon’s information index (I) ranged from 1.293 for BR215 to 2.385 for B654, with an average of 1.908. The neighbor-joining tree, principal coordinate analysis, and Bayesian analysis revealed clear separation between hybrid cultivars and wild forms (Cluster/group I), as well as the differentiation within hybrid genotypes (Clusters/groups II and III). Additionally, the NJ dendrogram demonstrated a further split within Clusters/group III (III a and III b). Altogether, with the comparable SSR information of the European hazelnut cultivar ‘Barcelona’, the newly developed marker sets can assist in the germplasm identification of hazelnut cultivars and reproductive materials. Importantly, these combined SSR loci can be applied to characterize the genetic relationships and population structures among wild genotypes and hybrid cultivars, which will then provide information to guide hazelnut breeding based on their genetic background.

1. Introduction

Hazelnut (Corylus L.) is an important nut crop and woody oil plant with high economic and nutritional value. The genus Corylus is a member of the Birch family, Betulaceae, and of the order Fagales. To date, 13 species are commonly recognized by taxonomists around the world. Among these, the European hazelnut, C. avellana L., is a species commercially cultivated in Turkey, Italy, the USA, Azerbaijan, Georgia, Chile, Spain, France, and Iran [1,2]. Experts have introduced some European hazelnut to China since the 1970s, but unfortunately, few suitable areas in China have been found for the commercial cultivation of European hazelnut up to now, due to the climatic condition [3]. In China, there are eight commonly considered hazelnut species, but only one of the species, C. heterophylla Fisch. (named Ping hazelnut in Chinese) has been well developed in terms of commercial cultivation, in some limited parts of northeast China. The nuts of Ping hazelnut are not suitable for the commercial kernel market due to their smaller size, thicker shell and lower kernel percentage than European hazelnuts. Ping’ou hybrid hazelnuts (C. heterophylla × C. avellana) are the products of interspecific hybridization between some excellent maternal trees of Ping hazelnut from northeast China and several paternal cultivars of European hazelnut introduced from Italy [4]. Dozens of cultivars were selected from up to 2000 seedlings after 6 years of cross-breeding, among which, 15 cultivars have been released and widely cultivated in around twenty provinces of China, over about 112,000 h2, since 2000. The commercial traits of the cultivars are significantly better than those of their maternal parent. Additionally, the cultivars can tolerate low temperatures during the winter, showing a stronger adaptation ability than their paternal parent [4]. According to the genetic background of cultivars of Ping’ou hybrid hazelnuts, some traits of the cultivars vary from each other in morphology and adaptation. On the contrary, however, it is difficult to distinguish between cultivars at the sapling stage. Thus, confusion regarding cultivars is one of the primary problems facing hazelnut production in China. Meanwhile, new cross-breeding works have been carried out by many Chinese researchers in recent years. New cultivars have been released, such as ‘Xianda 1’ by the Economic Forestry Research Institute of Liaoning Province, and ‘Jinzhen 1’ from Shanxi Agricultural University. A group of candidate cultivars are about to be released by the Research Institute of Forestry, Chinese Academy of Forestry. Thus, it is important and urgent that we develop a genetic identification method to characterize and distinguish the present cultivars and any possible future cultivars.
DNA markers are highly polymorphic and independent of environmental interactions, which are noted to be the best tools for understanding genetic diversity and relationships. SSR markers have the distinguishing features of multi-allelic, co-dominant inheritance patterns, reproducibility, high polymorphism, locus specificity, and transferability to related species and genera [5]. At present, more than 700 SSR loci have been developed in Corylus [6,7,8,9,10,11,12,13], and have been widely used in population structure assessment [14,15,16], germplasm identification and genetic diversity analysis [17,18,19,20], linkage map construction [21,22,23,24], and molecular marker-assisted selection [25,26]. In our previous study, we identified some cultivars of Ping’ou hybrid hazelnut by using the EST-SSR markers we developed in a pistil transcriptome [27]. All the present cultivars could be identified by four markers, showing the efficiency of the EST-SSR markers. However, no samples of other species were used in the study, limiting the universal application of the cultivar identification method.
‘Barcelona’ is a European hazelnut cultivar that is commonly used in genetic relationship research [23,28,29,30], and its SSR loci information is also available online “www.ars.usda.gov/pacific-west-area/corvallis-or (accessed on 20 May 2023)”. In the present study, we collected 46 accessions of Ping’ou hybrid hazelnut, 1 accession of ‘Barcelona’, 5 accessions of C. heterophylla, 3 accessions of C. mandshurica, and 2 accessions of C. kweichowensis for SSR marker-based genetic analysis. Based on the fingerprinting of ‘Barcelona’ in this study, the published SSR data of ‘Barcelona’ was used to adjust the allele sizes. The objective of this study was to identify the present cultivars of the Ping’ou hybrid hazelnut, assess their genetic diversity level and genetic relationships, and develop a universal cultivar-identifying method for Corylus.

2. Materials and Methods

2.1. Plant Materials

A total of 57 samples were used in this study (Table 1), including 46 accessions of Ping’ou hybrid hazelnut, 1 accession of ‘Barcelona’, and 5, 3 and 2 accessions of C. heterophylla, C. mandshurica and C. kweichowensis, respectively. The samples of 42 accessions of Ping’ou hybrid hazelnut and 10 of wild Corylus species were collected from the hazelnut repository of the Chinese Academy of Forestry, Yanqing District, Beijing. Young, tender, and healthy leaves of each selected accession were collected in the early summer of 2020, immediately placed in liquid nitrogen, and brought back to the laboratory. The samples were stored at −80 °C until DNA was extracted. ‘Barcelona’ was collected from National Clonal Germplasm Repository, Corvallis, Oregon, USA in September 2019. Fresh and healthy leaves were selected, cleaned and dried in a freeze drier, then stored in silica gel until DNA was extracted. Samples of ‘Liaozhen 5’ and ‘Liaozhen 6’ were collected from the hazelnut repository of Shenyang Agriculture University in the summer of 2020. The samples of ‘Xianda 1’ and ‘Jinzhen 1’ were collected directly from breeders from the Economic Forestry Research Institute of Liaoning Province and Shanxi Agricultural University, respectively. Of those samples, fresh and healthy leaves were selected in the summer of 2020, and stored in silica gel until DNA was extracted.

2.2. DNA Extraction and PCR Amplification

DNA was extracted using a modified cetyltrimethylammonium bromide (CTAB) extraction method described by Zong et al. [14]. The purified total DNA was quantified via gel (1.0%) electrophoresis, and its quality verified via spectrophotometry. Then, all the DNA samples were diluted using dd H2O with a concentration of 10 ng/µL, and were stored at −20 °C for later PCR amplification.
A total of 72 SSR primers that were previously reported to be polymorphic by Oregon State University, USA (Table S1) were used to select the high efficiency SSR primers in this experiment, using the DNA samples of ‘Dawei’, ‘Yuzhui’, ‘Liaozhen 3’, and ‘Barcelona’. The annealing temperatures were used as suggested in the references [11,12,19]. Of the 72 SSR primers, 38 generated the expected polymorphic alleles on PAGE gels, among the five samples that were selected to analyze the genetic polymorphism of all the accessions. The forward and reverse primers were labeled with the fluorochrome of FAM or HEX (Table 2). The most suitable annealing temperatures of these primers were tested individually via the amplification of the DNA of ‘Dawei’ to ensure the accuracy of the multiplex PCR. Grouping information for the multiplex PCR as well as the post-PCR multiplexing for capillary electrophoresis is shown in Table S2. After the amplification in all accessions, six primers, i.e., B702a, B758, B779, B795, BR359 and GB423, were discarded after genotyping all the 57 hazelnut samples for complicated allele scoring due to large allele bin width, consecutive alleles, stuttering, and split peaks. Five primers, i.e., BR423, GB437, GB673, GB808 and GB867, were discarded for the relatively low PIC values in this experiment, as compared with other primers. The remaining 27 primers were subsequently tested for their ability to detect polymorphisms in 57 accessions.
PCR amplification was performed in a total of 20.0 μL volume that contained 2.0 µL of plant DNA, 0.4 µL of each dNTP (2.5 mM), 0.3 µL of forward primer (20 µM), 0.3 µL of reverse primer (20 µM), 2.0 µL of 10 × PCR buffer (containing MgCl2), 0.2 µL of Taq polymerase (TaKaRa), and dd H2O 14.8 µL. PCR amplification was performed with the following cycling parameters: a pre-denaturation step at 94 °C for 5 min, 35 cycles of 94 °C for 30 s, annealing at 57 °C~63 °C for 40 s (a different primer annealing temperature, see Table 2), 72 °C for 40 s, and a final extension at step 72 °C for 3 min.

2.3. Microsatellite Analysis

Amplified fragments of SSRs were analyzed separately with an ABI 3730XL capillary sequencer (Applied Biosystems, Foster City, CA), along with the GeneScan-500 LIZ size standard (Applied Biosystems, Foster City, CA). Post-PCR multiplexing of 4–6 primer pairs in a single well was used according to the fluorescent label and the size ranges of the products. For multiplexing, 2.0 μL of the PCR products from each primer pair were mixed and diluted with water to make a final volume of 150.0 μL. An aliquot of 1.0–1.5 μL of the multiplex was used for the capillary electrophoresis. The SSR allele sizes were called with GENEMAPPER software (version 4.0, Applied Biosystems) for all samples, and entered in a spreadsheet. The allele sizes read by the software were rounded up or down manually according to the reported SSR loci data of ‘Barcelona’. PCR amplification and capillary electrophoresis were repeated if the initial PCR failed or the result was ambiguous. the size standard

2.4. Data Analyses

The codominant SSR data were analyzed using MICROCHECKER software [31] for detecting null alleles at each locus for each population. Population genetic analysis was performed using POPGENE v.1.3.2 [32] to calculate the diversity parameters, including number of alleles (N), effective number of alleles (Ne), Shannon’s information index (I), Nei’s gene diversity (H), observed heterozygosity (Ho), and expected heterozygosity (He). The polymorphism information content (PIC) of each locus was computed using the Excel Microsatellite Toolkit [33].
Based on the presence or absence of a binary data matrix, a pairwise genetic distance matrix was calculated for all individual accessions using GENALEX 6.5 [34]. Then, a genetic clustering analysis based on the genetic distance matrix was carried out to generate a neighbor-joining (NJ) dendrogram representing the genetic relationships among accessions in MEGA 6 [35]. Furthermore, principal coordinate analysis (PCoA) was conducted to identify genetic variation patterns among the hazelnut genotypes in GENALEX.
A separate analysis of population genetic structure was conducted using a Bayesian model-based clustering strategy implemented in STRUCTURE 2.3.4 software [36]. This method uses a Markov Chain Monte Carlo (MCMC) algorithm to cluster individuals into populations on the basis of multi-locus genotype data. For STRUCTURE analysis, all accessions were initially assigned to 49 groups: 45 Ping’ou hybrid hazelnut accessions (1–45), 2 C. avellana accessions (46), 5 C. heterophylla accessions (47), 3 C. mandshurica accessions (48), and 2 C. kweichowensis accessions (49). The number of clusters (K) was estimated by performing 10 independent runs for each K (2–20), using 100,000 MCMC repetitions and 50,000 burn-in periods. We used the admixture model with correlated allele frequencies to account for possible ancestral admixture. The most optimal K value was determined using the ∆K method [37], as implemented in STRUCTURE HARVESTER [38].

3. Results

3.1. SSR Polymorphism and Genetic Diversity

Some 57 hazelnut accessions were successfully amplified by all the 27 SSR primer pairs (Table 3), and each genotype displayed unique fragment size at one or several loci (Table S3). This indicated that the combination of these 27 primers could be used well for the cultivar identification of hazelnut accessions in China. Fingerprints of most primers (17 loci) tested in ‘Barcelona’ had an identical fragment size to data downloaded from the reference or from NCGR website, while the rest of the 10 loci showed 0–4 bp differences. A total of 301 alleles were detected at all 27 loci, and the number of effective alleles (Na) varied from 6 for KG817 and GB818 to 18 for B654, with an average of 11.2. All markers showed a high level of polymorphism, as indicated by mean values for observed heterozygosity (Ho = 0.8415), expected heterozygosity (He = 0.8074), and polymorphism information content (PIC = 0.7762). Half of the loci showed high PIC values (>0.80) in the experiment. Moreover, the Shannon’s information index (I) ranged from 1.293 for BR215 to 2.385 for B654, with an average of 1.908 (Table 3).

3.2. Genetic Relationships among Accessions

To interpret the genetic relationships among diverse Corylus accessions, an NJ cluster analysis based on the Jaccord’s similarity coefficient was performed. The unrooted dendrogram revealed three major clusters (Figure 1). Fourteen accessions, including ten accessions of three wild species (C. heterophylla, C. kwechowensis, and C. mandshurica), one accession of ‘Barcelona’, and three accessions of Ping’ou hybrid hazelnut (‘Pingdinghuang’, ‘Liaozhen 5’, ‘Liaozhen 6’), were clearly divergent from the rest and closely clustered into Cluster I. Twelve hybrid accessions constituted Cluster II, among which ‘Dawei’ and ‘Yuzhui’ were excellent cultivars widely cultivated in north China. Cluster Ⅲ comprised all the remaining 31 hybrid accessions, indicating that the majority of the hybrid cultivars had high genetic similarity. Moreover, we found that Cluster Ⅲ could further be divided into two subclusters, Ⅲ a (18 accessions) and Ⅲ b (13 accessions), with accessions in each subcluster showing closer genetic relationships.
PCoA was performed to check the displacement of the accessions and to further confirm the clustering pattern obtained from the dendrogram (Figure 2). The first two PCs explained 47.38% of the cumulative variance among accessions, with PC1 accounting for 34.58% of the variance and PC2 for an additional 12.8%. The two-dimensional projection defined by the first two PCs of 57 hazelnut accessions also showed a similar clustering pattern to that of the NJ dendrogram. All accessions were grouped into three parts according to their genetic distance along the two axes. Apparently, the wild genotypes showed a tendency to separate from the hybrid hazelnut. Additionally, the hybrid accessions were separated into two main groups, corresponding to two clusters (II and Ⅲ) in the phylogenetic tree. Information on genetic relationships among breeding accessions is essential for plant breeders to efficiently improve species.

3.3. Population Stratification and Genetic Admixture

The 57 hazelnut accessions were further evaluated for population stratification and admixture analyses using a Bayesian model with STRUCTURE software (Figure 3). SSR data were analyzed, increasing the number of subgroups (K) from 2 to 20. The estimation of ΔK revealed the highest value for K = 3 (ΔK = 34.43) (Figure S1), suggesting the existence of three major groups. Group I accounted for 24.5% of all accessions, and it included ten accessions belonging to three wild species, one accession of Barcelona, and three hybrid accessions. Group II contained 12 hybrid accessions, while Group III comprised the remaining 31 hybrid accessions. At K = 2, these 57 accessions were divided into two groups, with Groups II and III identified at K = 3 assembled into a large group. When K = 4, Group II further split into two subgroups. Generally, the Bayesian clustering analysis strongly confirmed the results of the NJ dendrogram (Figure 1) and the PCoA scatterplot (Figure 2). Simultaneously, genetic admixture was observed among accessions, especially within Groups II and III. For instance, Ping’ou 28, Ping’ou 48, Liaozhen 4, and Liaozhen 8 of Group II showed some genetic admixture with accessions of Group I, while Jinzhen 1 of Group III shared similar ancestral components with the accessions of Group II. We believe that the admixture among accessions is due to artificial hybridization in the process of hazelnut breeding in China.

4. Discussion

Assessment of trueness-to-type through phenotypic observation is very difficult, and mistakes during the several steps of nursery plant propagation are costly. Therefore, developing a reliable DNA fingerprinting set for verifying the identity of hazelnuts would provide a crucial tool for verifying cultivar integrity in propagation systems and in hazelnut collections, and for protecting of breeders’ rights. Molecular markers are highly useful in the precise identification of landraces, hybrids, and wild genotypes; this facilitates their planned utilization in hybrid breeding programs. In recent decades, various DNA-based molecular markers (e.g., RAPD, RFLP, AFLP, SSR, ISSR, etc) have been used in crop plants. The amplicon fragment analysis of these markers is gel-dependent, and has a limited ability to rapidly assay large numbers of marker loci. However, recent improvements in molecular marker technology, such as fluorescence-based automated DNA detection and fragment sizing, enable cost-effective genotyping to characterize the germplasm for crop improvement. For example, ITS regions, the pthN gene, and CP gene were designed to detect strains of fungal, bacterial, and viral pathogens of cotton [39]. Multiplex molecular markers (11 RAPD, 11 ISSR, and 12 SSR) revealed a high polymorphism and significant differentiation across 20 commercial banana cultivars [40]. SSR and RAPD primers were used to evaluate the diversity and identify duplicates/misnomers among diverse grape accessions [41,42].
Of the various DNA markers, microsatellites or simple sequence repeats (SSRs) have become the marker of choice because of their advantages over other marker systems. SSRs are tandemly repeated 1–6 bp sequence motifs. They are abundant and dispersed throughout the genome and can be found in both coding and noncoding regions. Valuable characteristics such as high polymorphism, co-dominance, sensitivity (even a small quantity of DNA can be amplified by PCR), transferability to related species and genera, reproducibility, and ease of scoring have led to the extensive use of microsatellite markers for fingerprinting [43]. The exchange of primer sequences allows other labs to work with the same loci. In recent years, microsatellites have been used for various applications in fruit and nut crops, such as cultivar identification, breeding record verification, management of germplasm collections and identification of duplicate accessions, and evaluation of genetic diversity.
Previous studies have indicated that SSR loci developed from European hazelnuts were highly conserved and universal in other Corylus species, e.g., C. heterophylla and C. kweichowensis [15], C. colurna [44], and C. mandshurica [14]. However, a very limited number of SSRs have been tested in Ping’ou hybrid hazelnut so far. In this study, the transferability of 38 pairs of SSR loci was evaluated for 57 hazelnut accessions, a diverse group containing the most comprehensive breeding germplasm in China. Some 27 primers were successfully shown to have produced amplified products of expected length in all individuals; of these, some SSRs showed low Ho and He values, and only a few alleles, such as B606, B733, and BR215 (Table 2). Accordingly, we suggest that a subset of loci be used for future fingerprinting studies, with a preference for loci that are easy to score, have high Ho, He, and PIC values, and have a low frequency of null alleles [45]. According to the criteria, 11 robust SSRs, i.e., B029b, B504, A640, B619, B654, B664, B726, B734, KG811, BR483, and GK663 were recommended as the prior polymorphic markers for hybrid hazelnuts. These loci generate products of different sizes, and with different florescent tags could be used in three multiplex sets. Based on 26 SSR loci, the average genetic diversity of hybrid hazelnut (Ho = 0.84, He = 0.81), averaged over all hybrid accessions, was slightly higher than that of its parents C. avellana (Ho = 0.67, He = 0.72) and C. heterophylla (Ho = 0.74, He = 0.82) [15,19], and simultaneously, higher than its congeneric species, C. kweichowensis (Ho = 0.67, He = 0.82) and C. mandshurica (Ho = 0.67, He = 0.79) [14,15]. The high levels of heterozygosity may result from the biological features of hazelnut, including sporophyte incompatibility, dichogamy, and vegetative propagation of superior genotypes [11]. In particular, hybrid hazelnuts are destined to have high heterozygosity due to their hybrid origins in C. heterophylla × C. avellana.
Nowadays, hybrid strains have become the dominant hazelnut resources in China, with more than forty cultivars cultivated successively. However, some critical issues have gradually surfaced with the acceleration of the breeding process. On one hand, the existing hybrid hazel cultivars (strains) are selected from a mixed progeny group of multiple female and male parents, and the genetic relationships among cultivars are quite complicated, making it difficult to distinguish them in morphology. On the other hand, the phenomena of synonym and the confusion of the cultivars is one of the primary problems in hazelnut production in China. Unsuitable or/and mislabeled cultivars are either cannot tolerant the extreme weather, causing some physiological diseases (such as freeze damage and branch shriveling), or are incompatible with the main cultivar and the pollinizer, resulting in different levels of yield loss. In this study, we constructed the first DNA fingerprint for Ping’ou hybrid hazelnuts using highly polymorphic SSR markers, and fragment sizes were subjected to clustering and structural analyses. Our results revealed significant genetic differentiation of the three gene pools, and each group constitutes an independent source of genetic variability and a valuable resource of hereditary properties for breeders. The clustering analysis showed a clear separation between wild (i.e., C. heterophylla, C. mandshurica, C. kwechowensis, and Barcelona) and cultivated genotypes (i.e., hybrid cultivars), except for ‘Liaozhen 5’ and ‘Liaozhen 6’. Similar phenomena were also discovered in closely related species, for instance, Martins et al. [46], Boccacci et al. [47], and Campa et al. [48] observed a clear separation of wild genotypes from cultivated forms in C. avellana, except for a special type Ca24. Particularly, based on chloroplast SSR loci, Martins et al. [49] discovered that most of the wild genotypes had unique haplotypes, whereas Ca24 shared the most common chloroplast haplotype with landraces. Hence, the data reinforce the hypothesis that wild genotypes hold unique genetic variations and can provide valuable genetic resources for hazelnut breeding.
In addition, the population structure of these 57 hazelnut accessions was best depicted through standard structure analysis at K = 3, where three possible subgroups were identified. In brief, SSR markers clearly distinguish wild genotypes in a more homogeneous subgroup, while most of the hybrid cultivars displayed some genetic admixture sharing coefficients of ancestry. These results are generally consistent with the hereditary property that hybrid cultivars receive from the artificial hybridization of C. heterophylla and C. avellana. Nonetheless, multiple analyses supported the status of distinct taxonomic units of hybrid hazelnuts, as shown in the NJ tree, PCoA scatter plot, and STRUCTURE inference. Moreover, our results revealed a high level of differentiation within hybrid hazelnuts, for instance, the two distinct clusters/groups (II and III) and further subclusters (III a and III b).
Altogether, with the comparable SSR information of ‘Barcelona’, SSR information as well as the genetic background of Ping’ou hybrid hazelnuts in China can be recognized and analyzed by other researchers; these newly developed marker sets will assist in identifying hazelnut cultivars and reproductive materials derived from characterized stands. Importantly, these combined SSR loci can be applied to characterize the genetic relationships and population structures among wild genotypes and hybrid cultivars, which can supply information for guiding hazelnut breeding based on their genetic background.

5. Conclusions and Implications

The present study screened a set of 27 pairs of markers from 72 SSR primers developed in European hazelnut, which was highly polymorphic in Ping’ou hybrid hazelnut and related wild species. It provides evidence for the potential transferability of EST-SSRs tween related hazelnut germplasm, indicating that species-related cross-amplification is a useful method for the application of SSR markers in this genus. Additionally, these 27 primers were verified to be efficient for genetic identification of 46 economically important cultivars of Ping’ou hybrid hazelnut in China. Based on the unique molecular bands of each accession, genetic analysis revealed a clear separation between hybrid cultivars and their wild relatives. In particular, we identified two major genetic lineages within Ping’ou hybrid hazelnut, as well as two sub-lineages within Cluster Ⅲ, which enabled an SSR-based population structure inference and a hybridity evaluation of the F1 hybrid cultivars.
The knowledge of this genetic background would be useful in designing strategies to improve the utilization of available genetic variation in the context of hazelnut breeding in China. The established genetic identification technique system will help to ensure the uniformity of the saplings in production, and protect newly released cultivars at present and in the future.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/f14071405/s1, Figure S1: ΔK values for different numbers of clusters (K) in STRUCTURE analysis; Table S1: Information on the 72 candidate SSR markers used in the study. Table S2: Grouping information for the multiplex PCR and capillary electrophoresis. Table S3: Allele sizes of 57 hazelnut accessions at 27 SSR loci.

Author Contributions

Conceptualization and methodology, Z.Y. and Q.M.; validation, Z.Y. and T.Z.; formal analysis, Z.Y. and L.L.; investigation and resources, S.H. and L.L.; writing—review and editing, Z.Y., L.J., L.W. and Q.M.; experimental, data analysis, and visualization, Z.Y., Q.M. and S.H.; supervision, T.Z. and L.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Key R&D Program of China (2022YFD2200400), the Key Research and Development Program of Hebei Province (21326804D) and the Key Science and Technology Program of Anhui Province (202103B06020017).

Data Availability Statement

Data are contained within the article.

Acknowledgments

We appreciate Shawn A. Mehlenbacher and Jacob W. Snelling from Oregon State University for sharing information on the SSR markers. We appreciate the help of Kim E. Hummer, Nahla V. Bassil, Barbara S. Gilmore, and April M. Nyberg from the National Clonal Germplasm Repository, Corvallis, Oregon, USA, for offering the leaf samples of ‘Barcelona’. We thank Wenxuan Dong from Shenyang Agriculture University for offering the leaf samples of ‘Liaozhen 5′ and ‘Liaozhen 6′, Daoming Wang from the Economic Forestry Research Institute of Liaoning Province for offering the leaf samples of ‘Xianda 1′, and Suoxing Liang from Shanxi Agricultural University for offering the leaf samples of ‘Jinzhen 1’.

Conflicts of Interest

The authors declare no conflict of interest.

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Forests 14 01405 g001 550
Figure 1. Unrooted neighbor-joining (NJ) dendrogram based on Nei’s genetic distance of 57 hazelnut accessions. All accessions were divided into three genetic lineages: Cluster I (red) included 11 accessions of four wild species and 2 accessions of Ping’ou hybrid hazelnut; Cluster II (blue) included 12 accessions of Ping’ou hybrid hazelnut; Cluster Ⅲ (green) included 31 hybrid accessions of Ping’ou hybrid hazelnut. Cluster Ⅲ was divided into two sub-clusters Ⅲ a and Ⅲ b.
Figure 1. Unrooted neighbor-joining (NJ) dendrogram based on Nei’s genetic distance of 57 hazelnut accessions. All accessions were divided into three genetic lineages: Cluster I (red) included 11 accessions of four wild species and 2 accessions of Ping’ou hybrid hazelnut; Cluster II (blue) included 12 accessions of Ping’ou hybrid hazelnut; Cluster Ⅲ (green) included 31 hybrid accessions of Ping’ou hybrid hazelnut. Cluster Ⅲ was divided into two sub-clusters Ⅲ a and Ⅲ b.
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Forests 14 01405 g002 550
Figure 2. Principal coordinate analysis (PCoA) for the first and second coordinates estimated for 57 hazelnut accessions. Different groups are shown by different colors, and are consistent with that of the NJ dendrogram.
Figure 2. Principal coordinate analysis (PCoA) for the first and second coordinates estimated for 57 hazelnut accessions. Different groups are shown by different colors, and are consistent with that of the NJ dendrogram.
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Forests 14 01405 g003 550
Figure 3. Population stratification and genetic admixture of 57 hazelnut accessions, as inferred by STRUCTURE, with three, four, and five populations (K = 2, K = 3, and K = 4). A single vertical line represents a single accession, and different colors indicate different groups. Segments of each vertical line represent the extent of admixture in an individual.
Figure 3. Population stratification and genetic admixture of 57 hazelnut accessions, as inferred by STRUCTURE, with three, four, and five populations (K = 2, K = 3, and K = 4). A single vertical line represents a single accession, and different colors indicate different groups. Segments of each vertical line represent the extent of admixture in an individual.
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Table
Table 1. Leaf samples used in this experiment.
Table 1. Leaf samples used in this experiment.
CodeNamePlaceCodeNameSource
1DaweiYanqing, Beijing30Ping’ou 90Yanqing, Beijing
2Yuzhui *Yanqing, Beijing31Ping’ou 119Yanqing, Beijing
3BokehongYanqing, Beijing32Ping’ou 124Yanqing, Beijing
4KuixiangYanqing, Beijing33Ping’ou 127Yanqing, Beijing
5PingdinghuangYanqing, Beijing34Ping’ou 140Yanqing, Beijing
6Liaozhen 1 *Yanqing, Beijing35Ping’ou 162Yanqing, Beijing
7Liaozhen 2 *Yanqing, Beijing36Ping’ou 202Yanqing, Beijing
8Liaozhen 3 *Yanqing, Beijing37Ping’ou 230Yanqing, Beijing
9Liaozhen 4 *Yanqing, Beijing38Ping’ou 237Yanqing, Beijing
10Liaozhen 5Shenyang, Liaoning39Ping’ou 360Yanqing, Beijing
11Liaozhen 6Shenyang, Liaoning40Ping’ou 376Yanqing, Beijing
12Liaozhen 7 *Yanqing, Beijing41Ping’ou 402Yanqing, Beijing
13Liaozhen 8 *Yanqing, Beijing42Ping’ou 415Yanqing, Beijing
14Liaozhen 9 *Yanqing, Beijing43Ping’ou 460Yanqing, Beijing
15Xianda 1 **Dalian, Liaoning44Ping’ou 545Yanqing, Beijing
16Jinzhen 1 **Taigu, Shanxi45Ping’ou 572Yanqing, Beijing
17Ping’ou 3Yanqing, Beijing46Ping’ou 617Yanqing, Beijing
18Ping’ou 10Yanqing, Beijing47Barcelona (C. avellana)Corvallis, OR
19Ping’ou 14Yanqing, Beijing48P1 (C. heterophylla)Yanqing, Beijing
20Ping’ou 15Yanqing, Beijing49P2 (C. heterophylla)Yanqing, Beijing
21Ping’ou 21Yanqing, Beijing50P3 (C. heterophylla)Yanqing, Beijing
22Ping’ou 28Yanqing, Beijing51P4 (C. heterophylla)Yanqing, Beijing
23Ping’ou 30Yanqing, Beijing52P5 (C. heterophylla)Yanqing, Beijing
24Ping’ou 33Yanqing, Beijing53M1 (C. mandshurica)Yanqing, Beijing
25Ping’ou 40Yanqing, Beijing54M2 (C. mandshurica)Yanqing, Beijing
26Ping’ou 48Yanqing, Beijing55M3 (C. mandshurica)Yanqing, Beijing
27Ping’ou 62Yanqing, Beijing56C1 (C. kweichowensis)Yanqing, Beijing
28Ping’ou 72Yanqing, Beijing57C2 (C. kweichowensis)Yanqing, Beijing
29Ping’ou 88Yanqing, Beijing
Note: Samples 1 to 46 are all Ping’ou hybrid hazelnuts (C. heterophylla × C. avellana). “*” indicates the main cultivars of Ping’ou hybrid hazelnut, “**” indicates the newly released cultivars.
Table
Table 2. Information of the SSR markers used in the study.
Table 2. Information of the SSR markers used in the study.
LociLGTmMotifForward PrimerReverse Primer
B029b160(GA)3CAATTTACACCTCAGGGAAGAGAAGTTCACCCAAGAAATCCAC
B504260–63(CT)8GCCATCTCCATTTCCCAACCGGAATGGTTTTCTGCTTCAG
A6401063–67(CT)15(CA)13TGCCTCTGCAGTTAGTCATCAAATGTAGGCGCCATATAATTGGGATGCTTGTTG
B606357–60(ACAT)6Ns(AG)16TCTTGTGGTTTAGCATACTTCTCGGAAGAAAGCAAGAAGAGAGGAGA
B613760–63(CT)16CGCGTTTTGAGTCCCTTTAGCTACCCGCCTGCGAGAAC
B619360(TC)21AGTCGGCTCCCCTTTTCTCGCGATCTGACCTCATTTTTG
B654857–60(GA)9Ns(GA)(GA)9Ns(GA)20Ns(GA)7TCGCATGGGTAATTTTCTCACTCATCATTTGGGTGCTTCAA
B6571157–63(AG)15GAGAGTGCGTCTTCCTCTGGAGCCTCACCTCCAACGAAC
B6641060–63(TC)21CAAAGCCGTCGACAACAGTTTGCATTTGATGCCGATAA
B702a460–63(CT)13CG(CT)3NsAGTTGGCGCTCGCTCTCTTTGCAGCTCAGATGGTTCAC
B716657(CA)4GACAT(GA)13Ns(GGT)4GAACATTGTCGTATGCGGACTTCTGTTTGTTGCGCATGATT
B720563(AG)14CTCTGTGTCGGCTTTCTGGTATAAACCTCACGCCACACCT
B726857–63(TC)16NNN(TA)9GGAAATGGCAAATCCGTCTAAACGTTTTGCCTTCCTTGTG
B733760(TC)15CACCCTCTTCACCACCTCATCATCCCCTGTTGGAGTTTTC
B7341057(TG)11(GA)10AAGGTCCTGTTTGTTGGATCTCTGTTTCTTTGACAACCTGCATT
B751760–63(GA)15AGCTGGTTCTTCGACATTCCAAACTCAAATAAAACCCCTGCTC
B758257–60(CT)15TAATTTAAGCTGCCGTGCAATGCAAAATTGCATTGCTCAT
B777957–63(GA)15AGGGAAGGGTGTAGGACGTTTCGTTTTCTCCACATCACCA
B779460–63(CT)18CGCTCTTGGACTTGGGATACTTGCAGCTCAGATGGTTCAC
B791357–60(AG)14CACCAGGACCCTGATACCATTCCACAATGATTTTGTGAAAAC
B795757–63(TC)8Ns(CT)7NsGACCCACAAACAATAACCTATCTCTGGGCATCATCCAGGTCTA
KG811260(GA)17GAACAACTGAAGACAGCAAAGAAGGCGGCACTCGCTCAC
KG817260(AG)11AAAGTTAGAAGGGTCATTTGTCAAGGTGGAGATTGTTGG
KG845963–67(TC)8NS(GT)8TATAGATGCCATGGGTGCAAACAAAAACTATCACTTGACCCACCTTCCCTCTTT
BR215860–63(CGC) 5TGAAATCTTCACCTCTTAAAAGATCCGGAATCTGAGCTGCCAAGTC
BR359463(TCT)5TACCTAACACAACAGCCACCACTCAGAATGGTAATTGCACCTTG
BR423463(GAA)6ACAAACCAAAGGGAGTGTGGCAAGCTTTCCATCATCGTCA
BR4831160–63(AG)12TTACCACCACTTTTCAACACCAGGTACATCAAAGAAGGGAGCAC
GB332960–63(CAG)5CCCTTCTACACGCAACACAAGGGCACTCTCACCAAACAAT
GB410460–63(ATCC)4ag(CCAT)4CCTCTACTATCTAGGAAGCCCCAACTTTGGCCTTTTGGACTTTG
GB423657–63(GAGC)5GTCAAAGCTGAGGAATGGTTTTTCGGTTGTCACTTGGTCAATTA
GB437460–63(GTGA)7GCTTCTTGGAGGGTTCTGCGCCAGAGCGTAAGAGAGAGAGA
GB673557–63(TCACCA)5CAACAATGGGAATGTTGCAGGGGCCAATAGCAAAAGTTCA
GB808460–63(CTG)7GCATAAACCACTCCAACTCCTCTTTGCTATCCCTACTCAGCTCC
GB818157–63(GAG)5GAAGTTGGGTTGGAAGCAGTTCGTCCTCTGCACACTCTCATAC
GB8671157–63(GGA)6CTTGGCAAAGCTACCCTCACACGCGTTCTCTCCTAACGAA
GB875563(GGA)9ATGATGATGAGGAGGAGGAGAACAAAATCAGGCATACAGAACCA
GK6.63660–63(GA)18GCAAACTTCCAGAAAACCAAAATGTTCGTAGGACAACTGCAT
Note: “LG” indicates linkage group. “Tm”, annealing temperature. Tm of the primers was tested in this experiment.
Table
Table 3. Characteristics of the polymorphic SSR markers used in the study.
Table 3. Characteristics of the polymorphic SSR markers used in the study.
NameNaNeIHoHePICSize 1 (bp)Size 2 (bp)Size 3 (bp)Fingerprints 1Fingerprints 2Comparison of Fingerprints
B029b137.04012.18850.91230.86550.8435115–141115–143115–143122 *128 *121127−1 bp
B504126.85442.13850.91230.86170.8386161–187144–182144–188158182158182identical
A640137.35072.19640.98250.87160.8498354–378350–374350–378354374350370−4 bp
B606114.20941.79110.35710.76930.7330264–280258–280258–280270274270274identical
B61393.63381.59600.69640.73130.6898192–216184–206184–216200202198200−2 bp
B619136.29042.11620.91230.84850.8250146–180145–177145–181156170157171+1 bp
B654187.29292.38510.94740.87050.8526276–302250–302250–302286302286302identical
B657125.89661.96231.00000.83780.8091202–234206–240202–240218222218222identical
B664158.09222.26240.96490.88420.8638186–218186–216186–218206216206216identical
B716144.06631.90010.68420.76080.7345199–221191–229191–229207207207207identical
B720114.65141.93590.82460.79200.7680155–191159–177155–191161167161167identical
B726168.25672.34850.94740.88670.8676199–237207–241199–2412132292132310/+2 bp
B73384.21131.60330.59650.76930.7277161–185161–179161–185171173171173identical
B734167.70822.28570.89470.87800.8575231–261217–259217–261255255257257+2 bp
B751106.12441.95480.85960.84410.8160137–161135–157135–161143153141153−2/0 bp
B777103.56251.62230.77190.72570.6834202–224200–224200–224202222202222identical
B791125.75041.99660.78950.83340.8046205–241219–226192–242221225222226+1 bp
KG811107.75422.12430.85960.87870.8571240–278240–274240–278258 *264 *256262−2 bp
KG81763.17751.38970.84210.69140.6437351–377351–371351–377353 *365 *353365identical
KG845104.36691.71870.94740.77780.7403212–246218–242212–246222 *242 *222242identical
BR21563.19311.29320.78950.69290.6293120–135117–132117–135123126123126identical
BR483146.96462.18391.00000.86400.8419282–318280–312280–318302310302310identical
GB33273.62011.50230.73680.73020.6831275–292275–292275–292283286283286identical
GB41083.09871.40530.73680.68330.6379160–190147–175147–191161169159167−2 bp
GB81865.24031.71770.98250.81630.7816129–144129–144129–144129144129144identical
GB87594.40541.77310.87720.77980.7475325–352334–358325–358340340340340identical
GK6.63126.55042.11890.89470.85480.830876–11677–11376–1169510195101identical
Average11.14815.53201.90780.84150.80740.7762
Notes: Size 1 shows the allele size range reported in the references; Size 2 shows the allele size range in this experiment; Size 3 shows the allele size range combined with the previous two columns. Fingerprints 1 shows the allele IDs of ‘Barcelona’ downloaded from the references or from the NCGR website (with a “*” mark); Fingerprints 2 shows the allele IDs of ‘Barcelona’ in this experiment.
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Yang, Z.; Zhao, T.; Liang, L.; Jiang, L.; Wang, L.; Hou, S.; Ma, Q. Genetic Analysis of the Cultivars of Ping’ou Hybrid Hazelnut (C. heterophylla Fisch. × C. avellana L.) in China Based on SSR Markers. Forests 2023, 14, 1405. https://doi.org/10.3390/f14071405

AMA Style

Yang Z, Zhao T, Liang L, Jiang L, Wang L, Hou S, Ma Q. Genetic Analysis of the Cultivars of Ping’ou Hybrid Hazelnut (C. heterophylla Fisch. × C. avellana L.) in China Based on SSR Markers. Forests. 2023; 14(7):1405. https://doi.org/10.3390/f14071405

Chicago/Turabian Style

Yang, Zhen, Tiantian Zhao, Lisong Liang, Lei Jiang, Lujun Wang, Sihao Hou, and Qinghua Ma. 2023. "Genetic Analysis of the Cultivars of Ping’ou Hybrid Hazelnut (C. heterophylla Fisch. × C. avellana L.) in China Based on SSR Markers" Forests 14, no. 7: 1405. https://doi.org/10.3390/f14071405

APA Style

Yang, Z., Zhao, T., Liang, L., Jiang, L., Wang, L., Hou, S., & Ma, Q. (2023). Genetic Analysis of the Cultivars of Ping’ou Hybrid Hazelnut (C. heterophylla Fisch. × C. avellana L.) in China Based on SSR Markers. Forests, 14(7), 1405. https://doi.org/10.3390/f14071405

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