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Article

Fluorescent SSR-Based DNA Fingerprinting and Molecular Identity Card Development for 69 Mandarin Accessions

by
Xiaoxiao Wu
1,
Shiman Wu
1,2,
Haimeng Fang
1,
Ding Huang
3,
Chuanwu Chen
1,
Binghai Lou
1,
Ping Liu
1,
Yang Tang
1,
Jing Feng
1,4 and
Chongling Deng
1,*
1
Guangxi Key Laboratory of Germplasm Innovation and Utilization of Specialty Commercial Crops in North Guangxi, Guangxi Citrus Breeding and Cultivation Technology Innovation Center, Guangxi Academy of Specialty Crops, Guilin 541004, China
2
College of Biology and Pharmacy, Yulin Normal University, Yulin 537000, China
3
College of Pharmacy, Guangxi University of Chinese Medicine, Nanning 530200, China
4
College of Agriculture, Guangxi University, Nanning 530004, China
*
Author to whom correspondence should be addressed.
Horticulturae 2026, 12(4), 445; https://doi.org/10.3390/horticulturae12040445
Submission received: 27 February 2026 / Revised: 24 March 2026 / Accepted: 2 April 2026 / Published: 3 April 2026
(This article belongs to the Section Genetics, Genomics, Breeding, and Biotechnology (G2B2))
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Abstract

To establish standardized DNA fingerprinting and molecular identification systems for mandarin citrus, we analyzed 69 mandarin accessions via fluorescent SSR capillary electrophoresis to construct DNA molecular fingerprints and unique molecular identity cards. Eighteen highly polymorphic SSR primer pairs were screened, yielding 239 genotype calls and 147 alleles. The number of amplified alleles per primer pair ranged from 4 to 18, with polymorphic information content (PIC) values varying from 0.411 to 0.650. Ten core primer pairs were further selected, achieving a discrimination rate of 65.2% (45 out of 69 accessions distinguished). Utilizing these fluorescent SSR markers, we established DNA molecular fingerprints and unique molecular identity cards for all 69 accessions. Among them, 45 accessions possessed unique fingerprints, whereas the remaining 24 indistinguishable accessions were clustered into six groups. Each cluster contained both wild (4 accessions total) and cultivated (20 accessions total) resources with high genetic similarity, which merits further investigation. This study provides a practical foundation for the authentication, conservation, and genetic relationship analysis of mandarin germplasm resources and establishes a technical framework for standardizing mandarin variety identification.

1. Introduction

Mandarin citrus (Citrus reticulata Blanco), commonly known by the Chinese names “huangguo” and “guanggan”, is distinguished by its loosely adherent peel and encompasses a broad spectrum of tangerine and mandarin cultivars [1]. As the most extensively cultivated citrus group in China, mandarins exhibit substantial genetic diversity [2], with their taxonomic framework anchored in the seminal work of Barrett and Rhodes, who delineated just three true Citrus species: C. medica (citron), C. grandis (pummelo), and C. reticulata (mandarin) [3]. China serves as both a primary center of origin and a genetic diversity hotspot for mandarins [4,5], harboring a rich assemblage of cultivars—including Ponkan, Satsuma mandarin, Shatangju, and Nanfeng tangerine—that encompass both monoembryonic and polyembryonic genotypes [6].
Traditional identification of citrus cultivars relies heavily on morphological traits, a practice that proves inherently challenging for accessions with highly similar leaf morphology, owing to strong subjectivity and susceptibility to environmental interference. Unlike other Citrus groups such as pummelo (Citrus grandis) or citron (C. medica), which exhibit relatively distinct morphological features, mandarin accessions display extensive morphological convergence. This convergence results from their long cultivation history, frequent natural and artificial hybridization, and the accumulation of bud sports over centuries of selection. Consequently, even closely related mandarin cultivars often share highly similar leaf, flower, and fruit traits, making accurate morphological discrimination particularly challenging even for experienced taxonomists. This intrinsic complexity underscores the need for DNA-based identification systems with high resolution and reproducibility.
To circumvent these limitations, modern molecular biological techniques have emerged as powerful tools, enabling convenient, accurate, and reliable cultivar discrimination at the DNA level. Among these techniques, simple sequence repeat (SSR) markers are particularly valued for their high polymorphism, excellent reproducibility, and codominant inheritance patterns [7,8,9]. Nevertheless, conventional SSR genotyping based on polyacrylamide gel electrophoresis (PAGE) is plagued by operational cumbersomeness, the use of toxic reagents, low detection efficiency, and an inability to precisely quantify fragment sizes—drawbacks that constrain its applicability in large-scale germplasm analysis. While higher-resolution methods such as genotyping-by-sequencing (GBS) and SNP arrays are increasingly available for fine-scale genetic analysis, SSR markers remain a cost-effective, transferable, and accessible tool for routine germplasm management, particularly in resource-limited breeding programs and germplasm bank operations. The FCE-based system established here balances resolution with operational feasibility for large-scale mandarin accession authentication.
Fluorescent capillary electrophoresis (FCE) technology has been developed to overcome the limitations of traditional PAGE-based SSR detection, enabling stable, high-throughput, and precise determination of amplified fragment sizes. While FCE-coupled SSR analysis has been successfully deployed for DNA fingerprinting, molecular identity (ID) development, and cultivar authentication in major crops such as maize and rice [10,11,12,13], its application in citrus remains relatively limited. Advances in molecular marker technologies have further solidified the status of SSR markers as pivotal tools for citrus cultivar authentication, with numerous studies demonstrating their utility across diverse citrus research contexts [14,15]. Previous studies have employed SSR markers for citrus authentication across diverse contexts, including genetic diversity assessment [16], genetic stability validation [17], genotype characterization [18], seedling purity testing [19], cultivar-specific fingerprint development [20], fingerprint database construction for mixed germplasm collections [21,22], marker development from genome-derived SSR loci [23], and DNA fingerprint generation for specific hybrid cultivars [24]. While these studies collectively demonstrate the utility of SSR markers in citrus research, they share two major limitations when considered from the perspective of mandarin cultivar identification. First, the majority rely on polyacrylamide gel electrophoresis (PAGE), which lacks the precision to accurately size amplified fragments and therefore cannot reliably discriminate closely related accessions such as bud sports. Second, no standardized, fluorescence-based capillary electrophoresis (FCE) system has been established specifically for mandarin citrus that systematically encompasses both wild and cultivated accessions. Addressing this gap is critical, as mandarins represent the most genetically diverse and economically important Citrus group in China, yet a unified molecular identification framework tailored to this group remains undeveloped.
Despite mandarins ranking as the second most consumed fresh citrus fruit in China, standardized SSR-based molecular identification systems tailored specifically for this group remain inadequately developed. Against this backdrop, the present study aims to establish DNA fingerprints and molecular ID cards for 69 mandarin accessions using FCE-based SSR markers. This work provides a foundational reference framework for standardized varietal authentication, germplasm conservation, and genetic relationship analysis of mandarins and their related citrus taxa, thereby supporting the sustainable development of the global citrus industry.

2. Materials and Methods

2.1. Materials

Sixty-nine mandarin accessions (detailed in Table 1) were collected from the Citrus Germplasm Resource Preservation Nursery of the Guangxi Academy of Specialty Crops (Guilin, China). The accessions were selected to represent the genetic diversity of mandarin citrus in China, encompassing three categories: (1) wild mandarins (e.g., ‘Guposhanyeju’, ‘Mangshanyeju’, ‘Daoxianyeju’) from primary origin centers; (2) traditional landraces (e.g., ‘Shatangju’, ‘Nanfengmiju’, ‘Biangan’); and (3) improved cultivars and bud sports (e.g., ‘Miyagawa’, ‘Zaoshushatangju’, ‘Clementine’). Taxonomic assignment followed the classification of Barrett and Rhodes [3] with reference to Swingle’s system [25]. For each accession, three individual trees were sampled, and leaf tissues were collected and pooled in equal proportions prior to DNA extraction to minimize intra-accession variation. All materials were propagated and maintained via grafting onto trifoliate orange rootstock to ensure genetic consistency. Fresh tissue samples were collected and immediately stored at −80 °C to preserve DNA integrity for subsequent analysis.

2.2. DNA Extraction

Genomic DNA was extracted from the stored tissues following the method described by Lin and Walker [26], with the following modifications: (1) the concentration of β-mercaptoethanol was increased from 0.2% to 1% (v/v) to reduce oxidative browning; (2) an additional chloroform-isoamyl alcohol (24:1) purification step was introduced after the initial extraction to remove polysaccharides and phenolic compounds; and (3) DNA pellets were dissolved in TE buffer (10 mM Tris-HCl, 1 mM EDTA, pH 8.0) instead of sterile water to enhance long-term stability. DNA quality was evaluated using 1.2% agarose gel electrophoresis (stained with ethidium bromide) to assess for degradation and contamination. The purity (A260/A280 ratio) and concentration of extracted DNA were determined using a nucleic acid-protein quantifier. Only DNA samples with an A260/A280 ratio of 1.8–2.0 (indicating high purity) were used for subsequent SSR amplification.

2.3. Primer Design and Synthesis

SSR loci were identified from the clementine (Citrus reticulata) genome assembly [27]. A total of 4232 SSR loci meeting the specified criteria were identified. From these, 96 primer pairs were designed using Primer 5.0 software, adhering to the following criteria: primer length of 20–24 bp, GC content of 40–60%, annealing temperature (Tm) of 57–62 °C, and expected amplicon size of 100–350 bp. All primers were synthesized by Sangon Biotech (Shanghai) Co., Ltd. (Shanghai, China), with the 5′ end of each forward primer labeled with a fluorescent dye (FAM, HEX, or ROX) to facilitate subsequent capillary electrophoresis detection.

2.4. Primer Screening

A three-step primer screening strategy was adopted to select high-quality polymorphic primers:
  • Preliminary screening: Primers were initially tested via 2% agarose gel electrophoresis using genomic DNA from six mandarin accessions that were selected to represent the morphological and genetic diversity of the collection. PCR was performed in a 25 μL reaction volume containing 1 μL of template DNA, 1 μL of each primer, 2 μL dNTPs, 10× PCR buffer, and 0.2 μL of Taq DNA polymerase. Thermal cycling conditions were 94 °C pre-denaturation for 5 min; 94 °C denaturation for 45 s, annealing at (56–62 °C) for 45 s for 35 cycles; 72 °C extension for 1 min; final extension at 72 °C for 10 min; and holding at 4 °C. Each PCR reaction was performed in duplicate to verify reproducibility. Primers that yielded clear, single-band amplicons without smearing and with reproducible results were retained for secondary screening.
  • Secondary screening: Candidate primers from the preliminary step were further evaluated using 6% denaturing polyacrylamide gel electrophoresis (PAGE) to assess polymorphism. The same six accessions were used. Gels were silver-stained for visualization. Each reaction was repeated twice, and primers exhibiting distinct banding patterns among the test accessions were considered polymorphic and retained for final validation.
  • Final validation: Primers with satisfactory performance in secondary screening were subjected to final validation using SSR fluorescent capillary electrophoresis (FCE) on the full set of 69 mandarin accessions. This step confirmed their polymorphism, amplicon stability, and suitability for large-scale fingerprinting analysis. Primers that produced clear, single-peak electropherograms with minimal stutter peaks and consistent amplification across ≥95% of accessions were selected for subsequent analysis.

2.5. Fingerprint Construction

Validated genotypes obtained from SSR primer amplification were used for DNA fingerprint construction. For each primer pair, the molecular weights of amplified alleles were sorted in descending order and assigned unique Arabic numerals (e.g., 1, 2, 3…) as genotype codes. An Excel-based DNA fingerprint map was generated, where the x-axis represented the molecular weights of amplified alleles for each primer pair, and the y-axis corresponded to the 69 mandarin accessions. This map provided an intuitive visualization of the DNA fingerprint profiles for all tested samples, enabling direct differentiation of accessions based on their allelic profiles.

2.6. Molecular Identity Card Construction

To establish standardized molecular identity (ID) cards, the amplified allele sizes of each primer pair were converted into unified numeric or alphabetic codes following a predefined rule:
  • For each primer pair, the fragment sizes of amplified alleles were first sorted in ascending order;
  • Unique band patterns (genotypes) among the 69 accessions were encoded sequentially using Arabic numerals 1–9;
  • When the number of unique band patterns exceeded 9, uppercase English letters (A, B, C, …) were used to represent the 10th, 11th, 12th, and subsequent patterns;
  • Null alleles (no amplification products) were denoted as “0”.
Finally, the codes corresponding to each selected core primer pair were concatenated in a fixed order to form a unique molecular ID card for each mandarin accession.

3. Results and Analysis

3.1. Primer Design and Screening

A total of 142 primer pairs were evaluated, comprising 96 newly designed pairs and 46 previously reported SSR primer pairs. Through the three-step screening process, 112 primer pairs produced clear amplification products in agarose gel electrophoresis. Among these, 95 exhibited polymorphic banding patterns on PAGE and were subjected to FCE validation. After FCE analysis, 70 primer pairs yielded stable, reproducible peaks across the 69 accessions and were retained. From these, 18 primer pairs showing the highest polymorphism (PIC ≥ 0.4) and consistent amplification were selected for detailed genetic diversity analysis.
For fingerprint construction, 10 of the 18 polymorphic primers were selected as core primers based on the following criteria: (1) PIC ≥ 0.5 (highly polymorphic) [28]; (2) consistent amplification across all 69 accessions (no null alleles in >5% of samples); (3) clear, single-peak electropherograms with minimal stutter; and (4) even distribution across the citrus genome to minimize linkage redundancy. These core primers were designated S01, S11, S13, S17, S18, S21, S73, S76, S85, and S90.

3.2. Genetic Diversity Analysis of 69 Mandarin Accessions

3.2.1. Polymorphism Evaluation of SSR Primers

Using the 18 polymorphic primer pairs selected from the screening process, fluorescent capillary electrophoresis was conducted on the 69 mandarin accessions. The amplified fragment sizes ranged from 122 to 369 bp, with a total of 147 alleles detected across all 18 loci. The average number of alleles per primer pair (Na) was 8.16, with allele counts per locus varying from 4 to 18. Primer S90 produced the highest number of alleles, while primers S76 and S85 yielded the fewest. A total of 239 genotypes (amplified bands) were identified from the 18 primer pairs, with 6–30 genotypes per locus. Notably, the number of genotypes exceeded the number of alleles for all 18 primer pairs, indicating high heterozygosity and polymorphism of these loci.
The effective number of alleles (Ne) ranged from 1.883 to 6.089, reflecting substantial variation in allele frequency and potential functional importance of these loci. Shannon’s information index (I), a key indicator of genetic diversity, averaged 1.410 across the 18 primer pairs, with 9 pairs showing values above this average. The average observed heterozygosity (Ho) was 0.532, confirming high genetic diversity within the 69 mandarin accessions.
Polymorphic information content (PIC) values were used to classify primer polymorphism: primers with PIC > 0.5 were defined as highly polymorphic, and those with 0.4 ≤ PIC ≤ 0.5 as moderately polymorphic. The average PIC value of the 18 primer pairs was 0.621, with 9 pairs exceeding this average. All 18 primers exhibited PIC values ≥ 0.411, among which 12 were highly polymorphic and 6 were moderately polymorphic, indicating that these primers carry rich polymorphism information and are suitable for mandarin genetic diversity analysis and fingerprint construction (Table 2).

3.2.2. SSR Characteristic Fingerprint Information of 69 Mandarin Varieties

Among the 69 mandarin accessions, 29 possessed unique alleles that were not detected in other accessions. These unique alleles could serve as diagnostic markers for distinguishing these accessions from others. The number of specific unique alleles varied among these 29 accessions, providing a basis for their rapid and accurate identification (Table 3).

3.2.3. Cluster Analysis

Based on polymorphism level, stability, and amplification efficiency, 10 primer pairs (S01, S11, S13, S17, S18, S21, S73, S76, S85, and S90) were selected as core primers for cluster analysis. A phylogenetic tree was constructed based on genetic distance using the unweighted pair-group method with arithmetic means (UPGMA), which clustered the 69 mandarin accessions into three distinct groups: Group I contained a single accession, ‘Yinduyeju’ (Code 7 in Table 1); Group II included 5 accessions, such as ‘Guposhanchougan’ (Code 11, Code 12, Code 13) and ‘Yuanyemangshanyegan’ (Code 14), ‘Jianyemangshanyegan’ (Code 15); Group III was the largest group, comprising 63 accessions, which were further subdivided into four subgroups. The clustering results were generally consistent with traditional citrus taxonomic classifications, reflecting the genetic relationships among different mandarin germplasms. Additionally, genetic differences were observed between certain wild accessions and cultivated hybrids, which may be attributed to the absence of distantly related germplasms (e.g., kumquat (Fortunella spp.) and trifoliate orange (Poncirus trifoliata)) in this study (Figure 1).

3.3. Construction of DNA Fingerprint and Molecular Identity Card

3.3.1. DNA Fingerprint Construction

For fingerprint construction, the 10 core primer pairs were used. These 10 primers generated 139 alleles and 225 genotypes across the 69 accessions. DNA fingerprints for the 69 mandarin accessions were constructed based on the validated genotypes and allele molecular weights determined by fluorescent capillary electrophoresis. Figure 2 presents the comprehensive DNA fingerprint map, where the vertical axis corresponds to the 69 mandarin accessions (with amplified alleles at each SSR locus), and the horizontal axis represents the molecular weights of amplified fragments across all tested loci. This map intuitively displays the distinct banding patterns of each accession, laying a foundation for rapid varietal discrimination.

3.3.2. Varietal Discrimination Using Core Primer Combinations

A single core primer pair (selected from the 10 core primers) failed to fully discriminate all 69 mandarin accessions. Among the individual primers, S90 exhibited the highest discrimination efficiency, distinguishing 20 accessions with a discrimination rate of 28.98%. When all 10 core primer pairs were combined, 45 out of 69 accessions (65.2% discrimination rate) were successfully differentiated (Table 4). The remaining 24 indistinguishable accessions were clustered into six groups, reflecting their close genetic relationships—likely attributed to conserved genomic sequences and similar genetic backgrounds, which may result from common ancestry or artificial selection.

3.3.3. Molecular Identity Card Construction

Following the predefined coding rule (numeric codes 1–9 and uppercase letters for additional genotypes, with “0” for null alleles), the amplified fragment sizes of the 69 mandarin accessions were encoded using the 10 core primer pairs (Table 5). This resulted in the generation of 69 unique molecular identity cards for the tested mandarin accessions (Table 6). Among these, 45 molecular identity cards were distinct, corresponding to the 45 discriminable accessions, indicating that these accessions possess unique allelic profiles that can serve as diagnostic markers for their accurate authentication. Finally, the codes corresponding to each selected core primer pair were concatenated in a fixed order (S76, S85, S73, S13, S11, S01, S18, S17, S21, S90) to form a unique molecular ID card for each mandarin accession. This order was maintained consistently across all ID cards to ensure comparability.

4. Discussion

Mandarin citrus (C. reticulata) has evolved diverse local accessions through long-term cultivation and breeding. Accessions derived from bud mutations or seedling selection often share highly similar genetic backgrounds, posing challenges for accurate identification. Molecular markers, which capture allelic variations, are therefore crucial for revealing genetic relationships among citrus germplasms. In this study, several accessions with known genetic origins were included: extra-early-maturing tangerine (bud sport of ‘Nanfeng’ tangerine), ‘Miyakawa Bun’ (bud sport selection of ‘Miyagawa’), ‘Miyagawa’ (bud sport of Satsuma mandarin), ‘Hashimoto’ (bud sport of ‘Matsuyama Satsuma’), ‘Shiwen’ and ‘Shanxiahong’ (bud sports of ‘Miyagawa’), ‘Mingliutianju’ (bud sport of ‘Chuntian’ tangerine), ‘Huacheng No.1’ (seedling selection of sweet orange), ‘Xinshengxi No.3 Ponkan’ and ‘Taitian Ponkan’ (seedling selections of Ponkan), ‘Dajin No.4’ (seedling selection of Satsuma mandarin), ‘Okitsu’ (nucellar line of ‘Miyagawa’), and the hybrid ‘Tsunoka tangor’ (cross of ‘Kiyomi’ × ‘Okitsu’). Our results showed that germplasms with identical SSR banding patterns clustered together, reflecting genetic conservation in citrus, while divergent allelic variation sites indicated genetic differentiation. Notably, cluster analysis revealed co-grouping of certain wild and cultivated accessions that deviated from traditional taxonomic classifications, suggesting complex genetic affinities among mandarin germplasms.

4.1. Genetic Diversity of Mandarin Germplasms

Simple sequence repeat (SSR) markers are widely recognized as robust tools for assessing plant genetic variation and have been extensively applied in fruit tree genetic diversity studies, including pear [29], apple [30], and persimmon [31]. In this study, we combined SSR markers with fluorescent capillary electrophoresis to analyze the genetic diversity of 69 C. reticulata accessions. The mean Shannon’s information index (I = 1.480) and polymorphic information content (PIC) values indicated substantial genetic diversity within the tested mandarin germplasms. The average PIC value observed for the 10 core primers (0.621) is comparable to values reported in SSR-based citrus diversity studies by Li et al. [22] (0.58–0.72), who analyzed a broader collection spanning multiple Citrus species, and higher than those reported by Lei et al. [21] (0.34–0.58), who focused primarily on cultivated citrus accessions. This discrepancy likely reflects differences in the genetic breadth of the sampled germplasm: the present study included a higher proportion of wild mandarins (11 accessions), which tend to harbor greater allelic diversity than cultivated accessions alone. Notably, eight loci in this study exhibited PIC values exceeding 0.65 (the threshold for high polymorphism), indicating their strong potential for citrus germplasm characterization. It should be noted that PIC values are material-dependent, as they vary with allele frequency differences across experimental samples. These diversity indices collectively reflect the magnitude of genetic variation, with higher values corresponding to increased heterozygosity—findings consistent with the rich genetic diversity of mandarins in China, a primary center of origin [4,5].

4.2. Insights from Cluster Analysis

The UPGMA dendrogram revealed three main clusters (Figure 1). Several patterns warrant discussion. First, wild mandarins were distributed across all three clusters rather than forming a single cohesive group, suggesting that the genetic differentiation among wild mandarins may be comparable to that between wild and cultivated forms. Notably, ‘Yinduyeju’ formed a distinct single-accession group (Group I), supporting previous suggestions that it may represent a primitive mandarin lineage [32] or a distinct taxonomic entity [25]. Second, accessions derived from bud sports (e.g., Satsuma mandarin and its derivatives, including ‘Miyagawa’, ‘Hashikawa’, and ‘Yoshida’) consistently clustered together, consistent with their shared genetic background and the minor genomic alterations underlying bud sport formation [33]. Third, some cultivated accessions clustered with wild mandarins—for example, ‘Biangan’ clustered with ‘Hezhouyeju’ within Group III—raising the possibility of introgression from wild populations into cultivated gene pools. However, given the limited number of SSR markers used (10 core primers), these observations should be interpreted as hypotheses for further investigation using higher-resolution genomic approaches such as whole-genome resequencing rather than definitive taxonomic or phylogenetic conclusions.
Wild-cultivated germplasm relationships revealed additional patterns: Group I contained a single accession, ‘Yinduyeju’; Group II included 5 accessions, such as ‘Guposhanchougan’, ‘Yuanyemangshanyegan’, and ‘Jianyemangshanyegan’; Group III was the largest group, comprising 63 accessions, which were further subdivided into four subgroups. The co-clustering of ‘Hezhouyeju’ and ‘Biangan’ with ‘Shatangju’ and Ponkan demonstrates genetic kinship, consistent with the hypothesis that some cultivated mandarins may have originated from or hybridized with local wild populations [34]. However, definitive relationships between wild and cultivated mandarins will require genomic-scale data to resolve.

4.3. Value of DNA Fingerprints and Molecular Identity Cards

DNA fingerprinting, which visualizes PCR-amplified molecular markers, is widely adopted for cultivar identification due to its efficiency, accuracy, cost-effectiveness, and reproducibility. Previous studies have established citrus fingerprint databases using SSR markers: Li et al. [22] screened 362 SSR primer pairs to identify 21 highly polymorphic core primers, constructing a fingerprint database for 500 accessions spanning the Papeda and Citrus genera (including citron, lemon, lime, mandarin, and sweet orange); Lei et al. [21] selected 12 diagnostic primers from 200 SSR pairs to build fingerprints for 70 cultivated citrus accessions (oranges, pomelos, ponkan, tangors). Expanding on these efforts, our study incorporated both wild and cultivated mandarin accessions, developing DNA fingerprints for 69 germplasms using SSR markers combined with fluorescent capillary electrophoresis. To enhance visual discrimination, we converted fingerprint data into intuitive binary matrices in spreadsheets—facilitating rapid accession comparison.
Molecular identity (ID) cards, which transform molecular data into unique alphanumeric codes, have been widely applied in crop cultivar authentication, initially in rice and soybean, and later extended to fruit trees such as apple and pear. Lei et al. [21] used polyacrylamide gel electrophoresis (PAGE) to convert gel banding patterns into binary (0/1) matrices, generating cultivar-specific fingerprint codes by concatenating alphabetically coded primer sequences. However, conventional PAGE only approximates DNA fragment sizes via molecular weight marker comparison, lacking precision. In contrast, fluorescence-labeled SSR capillary electrophoresis enables precise fragment sizing with superior accuracy, sensitivity, and efficiency—addressing the limitations of PAGE.
In this study, we used fluorescent capillary electrophoresis to obtain exact fragment molecular weights, coded amplicons in ascending order using Arabic numerals and uppercase letters, and concatenated these codes to create unique molecular IDs for the 69 mandarin accessions. Similar approaches have been successfully applied in other citrus-related studies: Wu et al. [15] constructed 22 pummelo molecular IDs via fluorescent SSR capillary electrophoresis; Gao et al. [35] developed scannable QR-code IDs for 314 apple accessions using 6 SSR markers; Tang et al. [36] built molecular IDs for 145 mango germplasms with 12 fluorescent SSRs. To optimize cost-efficiency, we implemented a tiered screening strategy: agarose gel electrophoresis for preliminary amplification validation, PAGE for polymorphism assessment, and fluorescent capillary electrophoresis for precise sizing—yielding 225 genotypes and 139 alleles. While the capillary electrophoresis-based molecular IDs require further validation for direct citrus cultivar authentication, they represent a standardized tool for germplasm discrimination, variety protection, and breeding.
While the molecular ID system developed here provides a standardized format for mandarin accession authentication, it is important to acknowledge its scope and limitations. The system is optimized for the specific set of 69 accessions included in this study. When applied to broader germplasm collections, the discrimination rate may vary, and the coding scheme may require recalibration to accommodate newly discovered alleles. Additionally, because the coding scheme is based on fragment size ranges observed in this specific panel, direct transfer of codes to other laboratories may require prior harmonization of allele sizing across platforms. Therefore, this system should be viewed as a flexible framework that can be expanded and refined as additional accessions are characterized and as inter-laboratory standardization efforts advance.

4.4. Limitations and Future Perspectives

Several methodological limitations should be acknowledged. First, despite the use of 10 core SSR primers, 24 of the 69 accessions (34.8%) could not be fully discriminated, forming six clusters of genetically indistinguishable accessions. This is a recognized limitation of SSR markers when applied to closely related germplasm, particularly bud sports, which arise from minimal genomic alterations that are often undetectable with a limited set of microsatellite loci [33]. Second, while FCE improves precision over PAGE, it remains less powerful than next-generation sequencing-based methods such as Target SSR-seq [37] or whole-genome resequencing for resolving fine-scale genetic differences among bud sports and nucellar lines. Third, the taxonomic assignments in Table 1 reflect current classifications, but the phylogenetic relationships among certain wild mandarins (e.g., ‘Yinduyeju’, ‘Mangshanyeju’) remain debated; the clustering patterns reported here should not be interpreted as definitive taxonomic conclusions without corroborating evidence from genomic data.
Future work will address these limitations by (1) expanding the germplasm scope to include more wild and cultivated mandarin accessions and establishing a comprehensive molecular ID database; (2) integrating advanced technologies (e.g., transposon display, target SSR-seq, and whole-genome sequencing) to improve bud sport discrimination; (3) validating the developed molecular IDs in multi-environment and multi-year trials to enhance their reliability for practical cultivar authentication; and (4) combining molecular IDs with phenotypic traits to resolve citrus nomenclature conflicts and clarify genetic relationships. These efforts will advance mandarin germplasm management, support intellectual property protection, and promote the sustainable development of the citrus industry.

Author Contributions

Conceptualization, X.W., S.W., B.L., P.L., C.C., H.F., Y.T., J.F. and C.D.; methodology, X.W., S.W., B.L., P.L., C.C., H.F., Y.T., J.F. and C.D.; software, X.W., S.W. and J.F.; validation, X.W., S.W. and C.D.; formal analysis, X.W., S.W. and H.F.; investigation, X.W., S.W., B.L., P.L., C.C., H.F., Y.T. and J.F.; resources, X.W., S.W. and J.F.; data curation, X.W., S.W. and C.D.; writing—original draft preparation, X.W., S.W., D.H. and C.D.; writing—review and editing, X.W., S.W., D.H., B.L., P.L., C.C., H.F., Y.T., J.F. and C.D.; supervision, X.W., B.L., C.C. and C.D.; project administration, X.W., B.L., C.C. and C.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by The National Natural Science Fund: U23A20198; Construction Project of Guangxi Characteristic Crop Experimental Station: TS202101; Project supported by the Shanghai Committee of Science and Technology, China: 23QA1410300; Guangxi Citrus Innovation Team Project of National Modern Agricultural Industrial Technology System: nycytxgxcxtd-2021-05; Fund Project of Guangxi Citrus Breeding and Cultivation Technology Innovation Center: 2024A002; the Science and Technology Major Project of Guangxi: Gui Ke AA22068092.

Data Availability Statement

Data is contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

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Horticulturae 12 00445 g001
Figure 1. UPGMA dendrogram of 69 mandarin accessions based on 10 core SSR primers.
Figure 1. UPGMA dendrogram of 69 mandarin accessions based on 10 core SSR primers.
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Figure 2. DNA fingerprint profiles of 69 mandarin accessions generated by fluorescent capillary electrophoresis.
Figure 2. DNA fingerprint profiles of 69 mandarin accessions generated by fluorescent capillary electrophoresis.
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Table 1. List of 69 experimental accessions.
Table 1. List of 69 experimental accessions.
CodeAccession NameScientific NameCodeAccession NameScientific Name
1GuposhanyejuC. reticulata36YingxinjuC. reticulata
2XinganyejuC. reticulata37PixejuC. reticulata
3DaoxianyejuC. reticulata38BendizaoC. reticulata
4MangshanyejuC. reticulata39Penggan No79-2C. reticulata
5NiuduyejuC. reticulata40Dong No13pengganC. reticulata
6HezhouyejuC. reticulata41Shi18pengganC. reticulata
7YinduyejuC. reticulata42TaitianpengganC. reticulata
8LihuajuC. reticulata43Xinshengxipenggan No3C. reticulata
9CengxisuanjuC. reticulata44WuhepengganC. reticulata
10GuangxihongpisuanjuC. reticulata45Dafen No4C. reticulata
11Guposhanchougan No2C. reticulata46Rinan No1C. reticulata
12Guposhanchougan No5C. reticulata47Dapu No5C. reticulata
13Guposhanchougan No6C. reticulata48MiyamotoC. reticulata
14YuanyemangshanyeganC. mangshanensis49MiyagawaC. reticulata
15JianyemangshanyeganC. mangshanensis50HashikawaC. reticulata
16ShaganC. reticulata51XingjinC. reticulata
17BianganC. reticulata52YoshidaC. reticulata
18BanyeshengganC. reticulata53IchibunC. reticulata
19HuangpisuanjuC. reticulata54YamasitabeniC. reticulata
20HongpisuanjuC. reticulata55KatsuyamanoC. reticulata
21ShatangjuC. reticulata56UenoC. reticulata
22ZaoshushatangjuC. reticulata57Dajin No4C. reticulata
23YamadaC. reticulata58ZaoxiangC. reticulata
24BayuejuC. reticulata59SakikuboC. reticulata
25DenglongjuC. reticulata60JinzhixiangC. reticulata
26JinkuimijuC. reticulata61YouliangC. reticulata
27Nanfengmiju1C. reticulata62ChunjianC. reticulata
28Nanfengmiju2C. reticulata63NanxiangC. reticulata
29TezaoshumijuC. reticulata64MurcottC. reticulata
30LiuchengmijuC. reticulata65GongganC. reticulata
31GuijuyihaoC. reticulata66WoganC. reticulata
32ClementineC. reticulata67HuangmeirenC. reticulata
33MingliutianjuC. reticulata68Aiyuan No38C. reticulata
34ChuntianjuC. reticulata69MingrijianC. reticulata
35GuangxijuC. reticulata
Table 2. Genetic diversity parameters of 18 SSR primers.
Table 2. Genetic diversity parameters of 18 SSR primers.
PrimerGenotypes (No.)NaNeIHoHePICSize Range (bp)
S011363.4921.4620.4930.7140.677282~307
S111062.3461.160.4920.5740.539172~191
S13862.5371.1110.3810.6060.527230~251
S171996.0891.8840.8330.8360.814166~200
S181593.7491.5170.6810.7330.689230~249
S2119114.5351.7800.6380.780.751244~269
S73972.1301.1410.5290.530.503344~369
S76642.0730.810.6960.5180.411168~186
S85841.8830.8890.4060.4690.432125~137
S9030184.7842.1090.5290.7910.776148~202
S231282.2601.2480.4350.5580.535139~189
S28962.8361.2390.3190.6470.582308~322
S7018144.4111.8540.7830.7730.747218~248
S711363.6141.4380.6810.7230.681211~237
S74862.3831.1510.3380.580.538182~203
S8115105.6781.9160.5070.8240.802167~192
S821793.0841.4370.3680.6760.622122~158
S841082.5571.2250.4710.6090.561265~292
Na: number of alleles; Ne: effective number of alleles; I: Shannon’s information index; Ho: observed heterozygosity; He: expected heterozygosity; PIC: polymorphic information content. Primers S01, S11, S13, S17, S18, S21, S73, S76, S85, and S90 were selected as core primers for fingerprint construction.
Table 3. SSR primers containing specific alleles.
Table 3. SSR primers containing specific alleles.
PrimerNumberAccession NameIdiotypePrimerNumberAccession NameIdiotypePrimerNumberAccession NameIdiotype
S012Yinduyeju307/307S707Guposhanyeju230/232S843Guposhanchougan No5170/170
Lihuaju282/283Hezhouyeju226/240Yuanyemangshanyegan279/279
S112Yinduyeju179/179Yinduyeju228/228Jianyemangshanyegan277/285
Biangan188/191Lihuaju224/224S9019Guposhanyeju165/171
S132Lihuaju230/245Huangpisuanju234/248Mangshanyeju161/165
Yinduyeju251/251Guijuyihao230/244Nieduyeju161/171
S175Biangan170/170Aiyuan No38220/226Hezhouyeju152/164
Banyeshenggan166/170S714Mangshanyeju219/234Lihuaju166/202
Zaoxiang180/184Yinduyeju211/237Guposhanchougan No2148/150
Wogan180/180Clementine237/237Guposhanchougan No5150/173
Aiyuan No38170/198Gonggan219/219Guposhanchougan No6148/173
S186Lihuaju247/249S742Yinduyeju191/191Shagan158/172
Guposhanchougan No5233/233Huangpisuanju182/203Biangan172/177
Yuanyemangshanyegan246/246S815Guposhanyeju169/174Huangpisuanju161/164
Jianyemangshanyegan243/246Mangshanyeju173/176Kelimandingju158/161
Katsuyamano231/239Hezhouyeju169/178Guangxiju161/161
Youliang237/243Yinduyeju170/170Pixeju161/173
S215Yinduyeju244/244Bendizao178/187Bendizao159/166
Lihuaju251/267S8213Nieduyeju140/147Katsuyamano157/161
Biangan255/259Yinduyeju147/147Jinzhixiang157/166
Banyeshenggan267/269Lihuaju122/150Gonggan158/166
Bendizao259/259Yuanyemangshanyegan140/153Aiyuan No38173/173
S236Guposhanyeju163/163Jianyemangshanyegan153/153S762Yinduyeju168/168
Nieduyeju163/169Huangpisuanju137/137Mangshanyeju180/186
Hezhouyeju169/189Kelimandingju134/150S854Guposhanyeju129/129
Yinduyeju139/139Pixeju134/134Mangshanyeju129/137
Lihuaju163/177Katsuyamano122/140Lihuaju129/133
Murcott169/169Gonggan134/140Guposhanchougan No5125/125
S281Yinduyeju312/132Wogan134/158
S732Jianyemangshanyegan345/345Huangmeiren128/158
Banyeshenggan366/366Aiyuan No38128/150
Table 4. Discrimination ability of 10 primer combinations.
Table 4. Discrimination ability of 10 primer combinations.
Primer CombinationNumber of Varieties IdentifiedDifferentiation Rate (%)
S902028.99
S90 + S182333.33
S90 + S112333.33
S90 + S172434.78
S90 + S012434.78
S90 + S732130.43
S90 + S212130.43
S90 + S852231.88
S90 + S11 + S132333.33
S90 + S76 + S11 + S17 + S132434.78
Total4565.22
Table 5. Allele size ranges amplified by SSR primers and encoding standard.
Table 5. Allele size ranges amplified by SSR primers and encoding standard.
CodeS76S85S73S13S11S01S18S17S21S90
1168/168125/125344/344230/230172/179282/283230/231166/170224/259148/150
2174/174125/133345/345230/245178/185282/296230/233170/170224/267148/173
3174/180125/137345/369239/245179/179282/299230/243170/180244/244150/173
4174/186129/129348/348239/248179/185283/283230/247170/182244/259152/164
5180/180129/133348/369242/242179/191283/290231/239170/184244/267157/157
6180/186129/137356/369242/248182/182283/296231/243170/198246/246157/161
7 133/133359/369245/245182/185283/299231/247172/172246/248157/166
8 133/137366/366245/248182/191290/290233/233172/182249/259158/161
9 369/369248/248185/191290/296237/243172/184251/267158/166
A 251/251188/191290/299243/243180/180255/259158/172
B 296/296243/246180/182259/259158/173
C 299/299243/247180/184259/267159/166
D 307/307246/246180/198259/269161/161
E 247/247180/200261/269161/164
F 247/249182/182263/263161/165
G 182/190263/267161/166
H 184/184267/267161/171
I 184/198267/269161/173
J 198/198269/269165/171
K 166/166
M 166/173
N 166/179
P 166/182
Q 166/202
R 172/172
S 172/177
T 172/179
U 173/173
V 176/179
W 179/179
Table 6. Molecular IDs for C. reticulata accessions based on SSR markers.
Table 6. Molecular IDs for C. reticulata accessions based on SSR markers.
Germless NameMolecular IDGermless NameMolecular ID
Guposhanyeju44998BABFJYingxinju37980274EV
Xinganyeju38985965DGPixeju33970970HI
Daoxianyeju38985965DGBendizao279808AHBC
Mangshanyeju669762CB8FPenggan No79-233573A7DHR
Niuduyeju279062A98HDong No13penggan33573A7DHR
Hezhouyeju38087374G4Shi No18penggan33573A7DHR
Yinduyeju173A3DA030Taitianpenggan33573A7DHR
Lihuaju359271F09QXinshengxi No3penggan33573A7DHR
Cengxisuanju37974378FPWuhepenggan33573A7DHR
Guangxihongpisuanju37974378FPDafen No4326938AI4K
Guposhanchougan No22215642F61Rinan No1376938AI4K
Guposhanchougan No52110848F63Dapu No5576938A04K
Guposhanchougan No62215842G62Miyamoto576008AI4K
Yuanyemangshanyegan273574D775Miyagawa379938AI4K
Jianyemangshanyegan222564B775Hashikawa376938AI4K
Shagan38785A43CAXingjin376938AI4K
Biangan5798ACE2ASYoshida376938A04K
Banyeshenggan37884971IKIchibun376938AI4K
Huangpisuanju3798437FHEYamasitabeni376938AI4K
Hongpisuanju32974378FPKatsuyamano2253175B56
Shatangju37933C74HTShangye376938AI4K
Zaoshushatangju37575C70HNDajin No4376038AI4K
Yamada376938AI4KZaoxiang325838CC5M
Bayueju37575C70HNSakikubo376938AI4K
Denglongju37930C74HTJinzhixiang3764151D47
Jinkuimiju37573C74HNYouliang376938904K
Nanfengmiju127985969CKChunjian3368384JHM
Nanfengmiju227985969CKNanxiang376948C55M
Tezaoshumiju27985969CKMurcott586859E3HW
Liuchengmiju27985969CKGonggan58583ACE59
Guijuyihao27985B6HCMWogan3809967AGW
Clementine3879453D58Huangmeiren3759386DGB
Mingliutianju37900274EVAiyuan No38389948465U
Chuntianju37989274EVMingrijian229845105B
Guangxiju32573A7EHD
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Wu, X.; Wu, S.; Fang, H.; Huang, D.; Chen, C.; Lou, B.; Liu, P.; Tang, Y.; Feng, J.; Deng, C. Fluorescent SSR-Based DNA Fingerprinting and Molecular Identity Card Development for 69 Mandarin Accessions. Horticulturae 2026, 12, 445. https://doi.org/10.3390/horticulturae12040445

AMA Style

Wu X, Wu S, Fang H, Huang D, Chen C, Lou B, Liu P, Tang Y, Feng J, Deng C. Fluorescent SSR-Based DNA Fingerprinting and Molecular Identity Card Development for 69 Mandarin Accessions. Horticulturae. 2026; 12(4):445. https://doi.org/10.3390/horticulturae12040445

Chicago/Turabian Style

Wu, Xiaoxiao, Shiman Wu, Haimeng Fang, Ding Huang, Chuanwu Chen, Binghai Lou, Ping Liu, Yang Tang, Jing Feng, and Chongling Deng. 2026. "Fluorescent SSR-Based DNA Fingerprinting and Molecular Identity Card Development for 69 Mandarin Accessions" Horticulturae 12, no. 4: 445. https://doi.org/10.3390/horticulturae12040445

APA Style

Wu, X., Wu, S., Fang, H., Huang, D., Chen, C., Lou, B., Liu, P., Tang, Y., Feng, J., & Deng, C. (2026). Fluorescent SSR-Based DNA Fingerprinting and Molecular Identity Card Development for 69 Mandarin Accessions. Horticulturae, 12(4), 445. https://doi.org/10.3390/horticulturae12040445

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