https://orcid.org/0009-0008-0232-681X
Figures
Abstract
Dali tea (Camellia taliensis), serving as a primitive wild species within the section Thea, represents a crucial genetic source for the domestication of Pu-erh tea (C. sinensis var. assamica) due to its strong stress tolerance and unique biochemical composition. It is of key value for the conservation of tea genetic resources and breeding innovation. Utilizing the SLAF-seq (Specific-Locus Amplified Fragment Sequencing) technique, this study systematically analyzed the genetic diversity and evolutionary relationships among five geographic populations (16 C. taliensis and 4 C. sinensis var. assamica accessions) within the Lancang River basin. Results revealed significant genetic differentiation among the C. taliensis populations. Pronounced genetic isolation was observed between the Lincang Daxueshan and Dali Nanjian populations. Localized gene introgression occurred between wild C. taliensis (Nanjian population) and C. sinensis var. assamica.The wild Lincang Daxueshan population formed a monophyletic clade at the base of the phylogenetic tree, exhibiting strong genetic isolation and high differentiation levels (Fst = 0.364) but low genetic diversity. In contrast, the cultivated population (Banna Germplasm Repository) displayed a mixed genetic background, with wild genetic components constituting only 50%−60%. The Lincang Daxueshan wild population showed a low minor allele frequency (MAF = 0.204) and a mild inbreeding coefficient (Fis = 0.09), indicating a potential risk of genetic erosion. Conversely, the Banna Germplasm Repository population exhibited the highest genetic diversity (Shannon Index = 0.318), highlighting the effectiveness of ex situ conservation and its potential as a vital gene donor for tea breeding. This study underscores the unique status of the upper Lancang River basin in Yunnan as a core conservation area for C. taliensis genetic diversity. We propose strategies of “delineating priority zones for in situ conservation” and “facilitating inter-population germplasm exchange,” providing a molecular basis for conserving wild tea resources and breeding for stress resistance. Employing high-density SNP markers, we obtained 5,182,931 loci with an average sequencing depth of 19.30x. This enabled quantification of gene flow between wild and cultivated populations (Nm = 0.18) and clarified the contribution of introgressive domestication to the genetic makeup of cultivated tea. These findings provide a theoretical foundation for understanding interspecific interaction mechanisms in tea plant evolution and hold significant implications for promoting regional ecological conservation and biodiversity maintenance.
Citation: Tao Y, Huang L, Chen H, Luo Y, Tang R, Li F, et al. (2025) Genetic diversity and evolutionary insights of Dali tea (Camellia taliensis) in the Lancang River Basin: Implications for tea breeding and resource conservation. PLoS One 20(7): e0328658. https://doi.org/10.1371/journal.pone.0328658
Editor: Ghulam Yaseen, University of Education, PAKISTAN
Received: October 10, 2024; Accepted: July 4, 2025; Published: July 31, 2025
Copyright: © 2025 Tao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are publicly available in the NCBI Sequence Read Archive (SRA) under accession number PRJNA1166700 (https://dataview.ncbi.nlm.nih.gov/object/PRJNA1166700?reviewer=vf1ede77gcukscli3ak5da3o2).
Funding: This study was supported by Yunnan Provincial Education Department fund project of China (2024J0670), Major science and technology project of Yunnan Province (202002AA100007), National Forestry and Grassland Administration sci-ence and technology project of China(2019130004-149).
Competing interests: The authors have declared that no competing interests exist.
Introduction
Dali tea (Camellia taliensis (W. W. Sm.) Melch.) [1,2], belonging to the section Thea of the genus Camellia L. (Theaceae), constitutes a vital component of tea germplasm resources. It harbors rich genetic diversity and holds irreplaceable value across multiple domains, including resource utilization, ecological conservation, cultural heritage, and scientific research [3,4]. Yunnan, recognized as the global center of origin and diversity for tea plants, hosts the Lancang River basin. Its unique geographical barriers and heterogeneous habitats have shaped the distinctive distribution pattern and genetic architecture of C. taliensis [5,6]. Due to the primitive characteristics of its leaf biochemical composition and its reservoir of stress-resistance genes, C. taliensis serves as a crucial wild gene pool for deciphering the domestication mechanisms of cultivated tea (C. sinensis var. assamica) [7–9]. However, due to over-harvesting and habitat fragmentation, wild populations of C. taliensis are confronting a dual crisis of genetic diversity loss and adaptive decline. The reduction in their effective population size may exacerbate the risk of inbreeding depression [10]. Currently listed as Vulnerable (VU) on the IUCN Red List [11], they urgently require precise conservation strategies informed by genomic data [12]. Although previous studies have partially revealed the population genetic characteristics of C. taliensis using SSR markers [13] and chloroplast DNA fragments [7], research on closely related Camellia species suggests that traditional molecular markers may underestimate the complexity of genomic structural variation [14]. This limitation hinders the resolution of key scientific questions: (1) Whether the phylogeographic differentiation pattern of C. taliensis within the Lancang River basin is coupled to the heterogeneity of its ecological corridors; (2) The spatiotemporal dynamics of gene flow between wild and cultivated populations and its contribution to domestication history; (3) The genomic distribution characteristics of candidate gene resources conferring adaptation to extreme environments. Recently, Huang et al. [14], employing reduced-representation genome sequencing, demonstrated that traditional molecular markers may underestimate the complexity of genetic structure in wild Camellias pecies. In contrast, genome-wide SNP marker systems can effectively uncover adaptive evolutionary trajectories at microgeographic scales [15]. Specific-Locus Amplified Fragment Sequencing (SLAF-seq) technology, based on targeted restriction enzyme site design, enables high-density SNP marker development even in the absence of a reference genome. Although its resolution is constrained by the distribution of enzyme recognition sites, its data throughput and cost-effectiveness are significantly superior to traditional sequencing approaches [16,17]. In practical applications for tea cultivation, this technology has successfully supported the identification of ancient tea tree resources [18] and the analysis of genetic structure in cultivated varieties [19]. However, its application to the conservation of wild tea germplasm resources remains subject to two major limitations: Firstly, existing studies still lack systematic analysis of the dynamic patterns of genomic introgression between wild and cultivated species; Secondly, a functional locus screening framework based on environmental adaptability has not yet been established, hindering the targeted utilization of wild gene resources in breeding programs. This study focuses on 16 wild C. taliensis populations from five geographic units within the Lancang River basin, alongside four cultivated C. sinensis var. assamica (Pu-er tea) accessions. Utilizing SLAF-seq technology, we aim to achieve the following objectives: (1) Construct a high-resolution genetic structure map of C. taliensis at the basin scale, revealing the geographic distribution pattern of its genetic diversity within the Lancang River basin; (2) Quantify the intensity of gene flow between wild and cultivated populations and characterize their genetic differentiation; (3) Provide preliminary genetic evidence to support in situ conservation strategies for C. taliensis germplasm resources. The findings will address the research gap concerning the interrelationships among baseline genetic diversity, population differentiation patterns, and conservation strategies for C. taliensis in the Lancang River basin. This will provide a molecular basis for the in situ conservation and sustainable utilization of tea genetic resources within this region.
Results and analyses
Restriction enzyme selection and library construction assessment
Using the C. sinensis genome as a reference, in silico restriction enzyme prediction was performed. The restriction enzyme HaeIII was ultimately selected, and fragments of 450–500 bp generated by digestion were defined as SLAF tags. Sequencing yielded 103.84 million (Mb) reads. Bioinformatic analysis developed 661,359 SLAF tags, of which 40,941 were polymorphic. Ultimately, 5,182,931 population-wide SNPs were obtained. Sequencing data quality parameters (Table 1) were validated by the Q30 value (average 93.32%), confirming data reliability suitable for subsequent analyses.
Development of SLAF tags and SNP markers
The average sequencing depth of SLAF tags obtained from the 20 tea germplasm accessions was 19.30× (Table 2). The number of tags per sample ranged from 154,203–259,806. Among these, sample SHC1 (C. taliensis from Shanhua Village, Nanjian, Dali) exhibited both the highest number of tags and the highest sequencing depth. Sample SNP completeness ranged from 42.05% to 58.32%, with observed heterozygosity levels between 11.67% and 16.91% (mean 14.29%). These values indicate relatively high genomic heterozygosity, supporting the suitability of the data for population genetic relationship analysis. Chromosomal distribution analysis revealed significant enrichment of SLAF tags in specific genomic regions, notably within a 74 Mb window on chromosome 10, a 55 Mb window on chromosome 2, and a 5 Mb window on chromosome 13 (Fig 1). This pattern suggests the potential presence of species-specific genetic variations within these chromosomal segments.
Note: Regions with increasing color intensity represent areas of concentrated SLAF tag distribution.
Analysis of population genetic structure
Phylogenetic structure analysis.
The phylogenetic tree is employed to delineate taxonomic and evolutionary relationships among species [20]. Phylogenetic reconstruction based on 16 C. taliensis and 4 C. sinensis var. assamica accessions from five prefectures within the Lancang River basin revealed two distinct major clades (Fig 2). Six C. taliensis accessions from the Lincang Daxueshan population (DLC1, DLC3, QT1, QT2, DXS1, DXS2) clustered within one clade, while the remaining 14 accessions (representing four other geographic populations) formed a separate major clade. Notably, the Lincang Daxueshan accessions (DXS1-DXS3, QT1-QT2) constituted a monophyletic clade with a homogeneous genetic background. In contrast, the cultivated accessions exhibited an admixed genetic background. The clustering pattern of the Pu’er Ailaoshan population accessions (MJ, LC) with germplasm from the Banna Repository (SX, ZYP833, ZYP866) showed a negative correlation with geographic distance (r = −0.32, P < 0.05), suggesting anthropogenic activities (e.g., germplasm introduction) may have disrupted natural dispersal patterns [21]. The strong concordance between geographic distribution and genetic clustering indicates closer kinship among individuals from the same locality. A weak genetic association was observed solely between C. taliensis from Dali Nanjian and C. sinensis var. assamica from Lincang Daxueshan, indicating potential localized interspecific gene flow.
Note: Accessions are colored by population: A (red) – Dali Wuliangshan; B (blue) – Baoshan Changning; C (green) - Pu’er Ailaoshan; D (purple) – Lincang Daxueshan; E (orange) – Banna Germplasm Repository. Letters denote sample identifiers.
Population structure and principal component analysis (PCA)
Population structure analysis is a widely used clustering method that quantifies the number of ancestral populations and infers the ancestry proportion of each sample [22]. Population structure analysis revealed that the cross-validation error rate was minimized at K = 2 (Fig 3). Accordingly, the 20 accessions were clearly partitioned into two distinct and cohesive genetic clusters (Fig 4). Cluster I comprised eight wild C. taliensis accessions from Lincang Daxueshan and Baoshan Changning (CSHCS, DLC1, DLC3, DXS1, DXS2, DXS3, QT1, QT2). This cluster exhibited a homogeneous genetic background, deriving entirely from a single ancestral population (Ancestor 1, represented by one color). Cluster II consisted of six accessions, including cultivated C. sinensis var. assamica and cultivated C. taliensis (CMQ, DYK2, MNZ, SHC1, SHC2, SM1). This cluster carried genetic information primarily from a second ancestral population (Ancestor 2, blue), indicating pronounced genetic divergence between wild C. taliensis and C. sinensis var. assamica. The remaining six accessions (MJ, LC, DYK1, ZYP865, ZYP833, SX) showed admixed ancestry. This suggests the introgression of wild genetic resources into some cultivated C. taliensis accessions, indicating unidirectional gene flow from wild to cultivated species. These individuals likely represent hybrids derived from the two ancestral subpopulations. However, accessions MJ, LC, and DYK1 retained ≥70% of the wild C. taliensis genetic background, classifying them as transitional types resulting from wild germplasm introgression. Cultivated C. taliensis accessions from the Banna Germplasm Repository (ZYP865, ZYP833, SX) retained relatively lower proportions of the wild C. taliensis genetic background, with ancestry contributions of 60%, 50%, and 50%, respectively. The wild Lincang Daxueshan population showed no further substructure at K-values ≥2, indicating its distinct genetic background with minimal or no gene flow from other species, supporting its genetic isolation. In contrast, populations from Baoshan Changning, Dali Nanjian, Pu’er Ailaoshan, and the Banna Germplasm Repository exhibited significant substructure, reflecting complex patterns of both interspecific and intraspecific gene flow. Principal Component Analysis (PCA; Fig 5) further corroborated the population structure results. C. taliensis and C. sinensis var. assamica accessions showed significant spatial separation along the principal components, confirming their distant kinship and substantial genetic divergence. With the exception of some overlap between C. sinensis var. assamica accessions from Baoshan Changning and Pu’er Ailaoshan, accessions from Lincang Daxueshan and Dali Nanjian were dispersed across the PCA plot. The distribution of C. taliensis accessions correlated strongly with their geographic origin. Accessions from Lincang Daxueshan and Baoshan Changning clustered tightly, while others showed genetic differentiation consistent with geographic isolation, aligning with conclusions from the phylogenetic tree and population structure analyses.
Note: The x-axis indicates the K-value (ranging from 1 to 10), while the y-axis displays the values of cross-validation error.
Note: The horizontal axis delineates 20 tea samples arranged sequentially, while the vertical axis indicates the number of subgroups denoted by K values (K = 1–10). Distinct colors are utilized to signify subgroups characterized by varying gene frequencies across the 20 tea plant samples, with tea plants within the same subgroup exhibiting close genetic relationships. The color assigned to each sample, along with its proportional representation, reflects the subgroup affiliation of the sample and the relative contribution of genetic material from that subgroup.
Note: Each point represents one sample. Points are colored by population: A (red) – Dali Wuliangshan; B (blue) – Baoshan Changning; C (green) - Pu’er Ailaoshan; D (purple) – Lincang Daxueshan; E (orange) – Banna Germplasm Repository.
Analysis of genetic diversity
Genetic diversity parameter analysis.
Studies of genetic diversity can elucidate the evolutionary history of species or populations (including their time and mode of origin) and provide critical insights for assessing their evolutionary potential and future trajectories [23]. Genetic diversity parameters for the five C. taliensis populations (Table 3) showed moderate levels for both the expected number of alleles (1.294–1.365) and the observed number of alleles (1.434–1.651). The mean expected heterozygosity (He) and observed heterozygosity (Ho) were 0.213 and 0.168, respectively. Nei’s diversity index ranged from 0.202 to 0.265 (mean 0.233), and the Shannon-Wiener index ranged from 0.251 to 0.318 (mean 0.290). The C. taliensis population from the Banna Germplasm Repository exhibited the highest values for expected number of alleles (1.365), expected heterozygosity (0.214), observed heterozygosity (0.245), Nei’s diversity index (0.265), and Shannon-Wiener index (0.318), indicating rich genetic diversity and potentially high environmental adaptability. The Baoshan Changning population ranked second (Shannon index = 0.298). In contrast, the Dali Nanjian, Pu’er Ailaoshan, and Lincang Daxueshan populations displayed relatively lower genetic diversity levels. The Lincang Daxueshan C. taliensis population showed significant minor allele frequency (MAF) depletion (MAF = 0.204, compared to 0.288–0.303 in other populations). Its observed heterozygosity (Ho = 0.172) and expected heterozygosity (He = 0.189) were lower than those of the cultivated Banna Repository population (Ho = 0.245, He = 0.214). The observed Ho < He in Lincang Daxueshan may reflect inbreeding or genetic drift [24]. While He exceeded Ho in most populations, the cultivated Banna Repository population exhibited the opposite pattern (Ho > He), suggesting it may have undergone unique genetic dynamics, such as artificial selection or significant gene flow. Furthermore, the Polymorphism Information Content (PIC) value reflects the ability of genetic markers to detect genetic variation. The PIC values across all five populations were low (0.135–0.171), indicating that the current markers have limited power for detecting genetic variation within these C. taliensis populations. Developing markers with higher polymorphism is necessary to enhance detection sensitivity. Overall, the analyzed C. taliensis germplasm resources exhibited moderate genetic diversity, likely associated with habitat heterogeneity and reproductive isolation within their contemporary distribution range.
Population differentiation and conservation priority.
Based on Wright’s [25] classification of the fixation index (Fst): 0 < Fst < 0.05 indicates low genetic differentiation; 0.05 ≤ Fst < 0.15 indicates moderate genetic differentiation; 0.15 ≤ Fst < 0.25 indicates high genetic differentiation; and Fst ≥ 0.25 indicates very high genetic differentiation. Pairwise Fst values (Table 4) revealed high differentiation between Dali Nanjian (A) and Baoshan Changning (B), Pu’er Ailaoshan (C), and Banna Repository (E), and very high differentiation with Lincang Daxueshan (D). Baoshan Changning (B) showed moderate differentiation with Pu’er Ailaoshan (C), Lincang Daxueshan (D), and Banna Repository (E). Pu’er Ailaoshan (C) exhibited moderate differentiation with Banna Repository (E) and high differentiation with Lincang Daxueshan (D). Banna Repository (E) showed high differentiation with Lincang Daxueshan (D). In summary, all pairwise comparisons indicated moderate to very high differentiation levels. Genetic differentiation between Lincang Daxueshan (D) and all other populations was exceptionally strong. This differentiation pattern correlates strongly with geographical isolation and habitat divergence. The isolated geography of Lincang Daxueshan likely impeded gene flow, confirming its unique status as a potential genetic refuge for C. taliensis [26]. Gene flow estimates indicated weak gene flow (Nm = 0.18) between Dali Nanjian (A) and Pu’er Ailaoshan (C), potentially reflecting unidirectional introgression from cultivated to wild types. Stronger gene flow (Nm = 1.30) occurred between Lincang Daxueshan (D) and Banna Repository (E), further evidencing genetic exchange facilitated by human intervention. The co-occurrence of low genetic diversity and high differentiation signals a risk of genetic erosion. Establishing ecological corridors to facilitate gene flow among populations is critical to enhance adaptive potential [27].
Discussion
Analysis of genetic diversity in C. taliensis from the Lancang River Basin and implications for conservation and breeding
Genetic diversity within germplasm resources forms the foundation for their utilization and exploitation in genetic breeding. Assessing the level of this diversity is crucial for identifying superior resources, selecting elite germplasm, and facilitating germplasm innovation in breeding programs [28]. The Polymorphic Information Content (PIC) reflects the level of diversity exhibited by a locus within a population [29,30]. According to standard interpretation [31], PIC > 0.5 indicates a highly polymorphic locus and high population genetic diversity; 0.25 < PIC < 0.5 indicates a moderately polymorphic locus and moderate genetic diversity; PIC < 0.25 indicates low genetic diversity. This study revealed a significantly lower average PIC value (PIC = 0.155) for C. taliensis populations in the Lancang River basin compared to previous studies. Mao et al. [32], investigating genetic diversity in wild and cultivated C. taliensis from three different populations, reported PIC values ranging from 0.041 to 0.877, with a mean of 0.491 (0.25 < PIC < 0.5), indicating moderate genetic diversity levels. Huang et al. [33], in a molecular identification study of 26 tea plant varieties under new plant variety protection application and 13 similar varieties, reported a PIC of 0.51 (PIC > 0.5) for these 39 tea germplasms, signifying high genetic diversity. Liu et al. [34] and Zhou et al. [35], analyzing tea plant resources from various regions and populations in Yunnan Province, documented PIC values reaching up to 0.527. However, our findings align with those of Ji et al. [36], who also studied Yunnan C. taliensis. This relatively low PIC likely stems from the natural attributes of C. taliensis as an endemic species with a narrow distribution. Habitat fragmentation restricts gene flow, and anthropogenic disturbances further exacerbate genetic isolation [36], reflecting the endangered status of this species. Notably, the mean observed heterozygosity (Ho = 0.181) across the five geographically distinct populations was lower than the mean expected heterozygosity (He = 0.194). This suggests prevalent inbreeding or genetic drift within the Lancang River basin C. taliensis populations. The Banna Germplasm Repository population exhibited the highest genetic diversity (Shannon index = 0.318), validating the effectiveness of ex situ conservation strategies [37]. Serving as a “genetic diversity hotspot,” this population offers valuable material for mining stress-resistance genes [38]. Conversely, the low minor allele frequency (MAF = 0.204) and mild inbreeding coefficient (Fis = 0.09) in the wild Lincang Daxueshan population signal a risk of genetic diversity erosion. Urgent measures, including delineating core areas for in situ protection and implementing assisted migration, are needed to maintain its evolutionary potential [39]. Our study also detected gene introgression (Nm = 0.18) between wild and cultivated populations. Populations such as Baoshan Changning and Pu’er Ailaoshan retained 70%−90% wild genetic components, while the Banna Repository population displayed an admixed background. This provides direct evidence supporting the hypothesis that cultivated C. taliensis may have originated through introgressive domestication from wild germplasm [40]. Prioritizing the use of these transitional types in breeding programs is recommended to enhance adaptability. Furthermore, the strong genetic differentiation (Fst = 0.364) between the Lincang Daxueshan and Dali Nanjian populations suggests they may have experienced divergent natural selection pressures or prolonged geographical isolation. Subsequent genome scans could identify adaptive genes, laying the groundwork for marker-assisted breeding.
Genetic structure analysis of C. taliensis in the Lancang River Basin and resource management strategies
Population structure analysis is indispensable in genetic diversity studies for elucidating genetic relatedness among germplasm resources and tracing the origins of specific genetic loci. Phylogenetic trees, a widely adopted approach, classify distinct germplasm accessions based on genetic proximity, thereby delineating kinship relationships and evolutionary trajectories. While Principal Component Analysis (PCA) enables intuitive visualization of genetic structure, it often lacks quantitative precision for determining optimal population subdivisions [41]. Single Nucleotide Polymorphism (SNP) markers are extensively employed in genetic map construction, genome-wide association studies (GWAS), and quantitative trait analysis due to their stability and abundance of genetic variation [42,43]. SNP-based population structure analysis revealed that the Lincang Daxueshan wild population forms a monophyletic clade occupying the basal position in the phylogenetic tree. This ancestral group subsequently diverged to generate the other four C. taliensis populations and the C. sinensis var. assamica group. This finding indicates that the Lincang Daxueshan population retains more ancestral genetic characteristics than other groups and underscores its significance in the historical domestication and utilization of C. taliensis. The observation that C. taliensis exhibits more primitive evolutionary traits than C. sinensis var. assamica aligns with morphological evolutionary pathways proposed for Sect. Thea species by Chen et al. [44]. This further suggests the region served as a glacial refugium for C. taliensis, with its genetic distinctiveness providing critical insights into tea plant origins [45]. Nevertheless, this population’s low genetic diversity and high differentiation imply constrained ecological adaptability. Strategic germplasm exchange across populations is thus essential to broaden its genetic base and enhance climate resilience [46]. Notably, the admixed clustering pattern between the Dali Nanjian population and C. sinensis var. assamica accessions supports the hypothesis by Li et al. [47] of C. taliensis involvement in Pu-erh tea domestication. Transcriptomic evidence from the Kunming Institute of Botany [2] corroborates this evolutionary relationship. We propose prioritizing the Nanjian population as a donor for interspecific hybridization to introgress wild-adaptive alleles. Furthermore, subpopulation differentiation within cultivated accessions (e.g., Xishuangbanna ZYP series) reflects anthropogenic reshaping of genetic architecture. Future breeding programs should emphasize geo-adaptive matching to prevent genetic homogenization from indiscriminate introduction [48]. Although SLAF-seq generated high-density SNP data, its genomic coverage bias toward gene-rich regions [18] likely underestimated diversity in repetitive and regulatory sequences. Additionally, rare alleles from peripheral populations were inadequately captured despite sampling major distribution zones. Subsequent research will employ whole-genome resequencing to detect structural variants and domestication signals, integrate phenomic data for genotype-phenotype association networks, and implement longitudinal monitoring to evaluate conservation efficacy.
Materials and methods
Materials
Plant materials comprised 16 accessions of C. taliensis and 4 accessions of C. sinensis var. assamica (Table 5) collected from five prefectures/cities within the Lancang River Basin. Sampling locations were selected based on the following criteria: 1) coverage of the geographic gradient from upper to lower reaches of the Lancang River Basin (elevation range: 1000–2700 m); 2) inclusion of both core distribution areas and marginal populations of C. taliensis; 3) use of C. sinensis var. assamica as a cultivated relative species for comparative genetic differentiation analysis. Sample size determination considered population distribution density within the basin and prior population genetics experience, ensuring a minimum of three biological replicates per geographic unit. Approximately 50 g of fresh, young leaves from the current year’s growth were flash-frozen in liquid nitrogen and subsequently stored at −80°C for future use. Four accessions of C. sinensis var. assamica (SHC1, DYK2, SM1, MNZ) were collected with prior permissions granted by the respective County Agriculture and Rural Affairs Bureaus and Village Committees in Nanjian, Changning, Jingdong, and Shuangjiang counties.Sampling of cultivated C. taliensis accessions (ZYP833, ZYP865, SX, CMQ, SHC2) was authorized by the Tea Germplasm Resource Garden, Xishuangbanna Dai Autonomous Prefecture Academy of Agricultural Sciences, and the Nanjian Yi Autonomous County Agriculture and Rural Affairs Bureau.Wild C. taliensis accessions CSHCS and DYK1 were collected under permit from the Changning County Forestry and Grassland Bureau.The remaining nine wild C. taliensis accessions were sampled with permissions obtained from the Management Bureaus of the Yunnan Ailaoshan National Nature Reserve and the Yunnan Lincang Daxueshan National Nature Reserve.All tissue sampling was conducted under the supervision of local agricultural and forestry field specialists. Samples were used exclusively for scientific research purposes. The non-invasive sampling methods employed in this study had no detectable impact on the natural growth of the Camellia plants.
DNA extraction and quality control
Genomic DNA was extracted from all 20 tea plant accessions using the Broad-Spectrum Plant DNA Extraction Kit (Biomad, Beijing, China). Extracted DNA was assessed for quality, concentration, and purity using a gel imaging analysis system and a UV spectrophotometer (Thermo Fisher Scientific, USA). All samples exhibited OD260/280 ratios between 1.8 and 2.0, with concentrations ≥ 30 ng/μL. Qualified DNA aliquots were stored at −20°C. Three technical replicates per sample were prepared for subsequent quality control procedures.
Enzymatic library construction
As the C. taliensis genome sequence is not publicly available, restriction enzyme digestion sites were predicted using the C. sinensis reference genome (available at http://tpia.teaplant.org/download.html#), based on the estimated genome size and GC content of C. taliensis. SLAF-seq (Specific-Locus Amplified Fragment Sequencing) was selected over GBS (Genotyping-by-Sequencing) or RAD-seq (Restriction-site Associated DNA Sequencing) based on: 1) the high polymorphism detection rate (>82%) of the HaeIII + MseI enzyme combination within the genus Camellia; 2) the flexibility to adjust tag density (target number of SLAF tags: 50,000); 3) suitability for population evolutionary analysis in complex genomes. Target fragments of 400–450 bp were predicted using SLAF_predict software. Following A-tailing of the 3’ ends, sequencing adapters were ligated [49]. The optimal number of PCR amplification cycles, determined by gradient optimization, was 12. Libraries passing quality control were subjected to paired-end sequencing (2 × 50 bp) on the Illumina HiSeq 2000 platform.
SLAF tag acquisition and SNP marker development
Paired-end reads were clustered into Specific Locus Amplified Fragment (SLAF) tags based on sequence similarity (≥95%) and positional consistency. To validate genotyping reliability, 5% of samples were randomly selected for replicate library construction and sequencing, achieving a genotype concordance rate of 98.5%. Polymorphic SLAF tags were filtered using the following criteria: 1) minor allele frequency (MAF) ≥ 0.05 across the population; 2) sequencing depth ≥ 4× per sample; 3) genotype call rate ≥ 85%. As tea plants are diploid, a single locus can harbor up to four genotypes. Therefore, SLAF tags containing two, three, or four alleles were classified as polymorphic. SNP markers underwent stringent quality control: 1) loci with abnormal heterozygosity (>30%) were removed; 2) loci significantly deviating from Hardy-Weinberg equilibrium (P < 0.001) were excluded; 3) markers in strong linkage disequilibrium (r2 > 0.8) were discarded. A high-confidence SNP dataset was ultimately obtained for downstream analyses.
Data analysis
Reads from all 20 samples were clustered based on sequence similarity, with groups of reads sharing high similarity defined as individual SLAF tags. SLAF tags exhibiting sequence variations among different samples were identified as polymorphic SLAF tags. The most frequent sequence variant within each SLAF tag served as the reference sequence. Sequencing reads were aligned to the reference genome using BWA [50]. SNP calling was performed independently using GATK [51] and SAMtools [52]. The intersection of SNPs identified by both methods constituted the final high-confidence SNP marker dataset. Population-specific SNP loci were subsequently identified through comparative analysis. Phylogenetic analysis was conducted using MEGA X [53]. A neighbor-joining tree was constructed under the Kimura 2-parameter model to infer evolutionary relationships among samples. Population structure was assessed using ADMIXTURE [54] (cross-validation replicates = 10). Principal Component Analysis (PCA) was performed using EIGENSOFT [55]. The reliability of all analytical pipelines was verified using positive controls.
Conclusions
This study employed SLAF-seq markers to develop SNP loci and analyze genetic diversity across 20 tea germplasm accessions from five geographic populations in the Lancang River Basin. Our results revealed significant geographic-genetic structuring within C. taliensis populations. Genetic introgression was detected between wild and cultivated groups. However, core wild populations (e.g., Lincang Daxueshan) exhibited latent risks associated with low genetic diversity. Low genetic diversity may compromise adaptive capacity to environmental change, necessitating prioritized establishment of in situ conservation sites to preserve gene pool integrity. Conversely, the high-diversity Xishuangbanna Germplasm Repository population represents a valuable genetic donor for tea breeding. Moderate to high genetic differentiation among populations underscores the need to consider genetic background differences during cross-regional germplasm introduction, preventing genetic homogenization through indiscriminate hybridization. This study provides a molecular theoretical framework for precision conservation of tea resources and parental selection in breeding. It particularly highlights the role of geographic isolation in shaping genetic structure, while expanding current understanding of interspecific gene flow and adaptive evolution in tea plant phylogenetics.
Acknowledgments
We express our profound gratitude to the following institutions for their indispensable assistance during fieldwork: Nanjian Yi Autonomous County Bureau of Agriculture and Rural Affairs, Changning County Bureau of Agriculture and Rural Affairs and Changning County Forestry and Grassland Bureau, Jingdong Yi Autonomous County Bureau of Agriculture and Rural Affairs, Shuangjiang Lahu-Va-Blang-Dai Autonomous County Bureau of Agriculture and Rural Affairs, Village Committees of Nanjian, Changning, Jingdong, and Shuangjiang Counties, Tea Germplasm Resource Garden, Xishuangbanna Dai Autonomous Prefecture Academy of Agricultural Sciences, Administration Bureau of Yunnan Ailao Mountains National Nature Reserve, Administration Bureau of Yunnan Lincang Daxueshan National Nature Reserve.
References
- 1. Chen L, Yu FL, Tong QQ. Discussions on phylogenetic classification and evolution of Sect∙Thea. J Tea Sci. 2000:89–94.
- 2. Zhang H-B, Xia E-H, Huang H, Jiang J-J, Liu B-Y, Gao L-Z. De novo transcriptome assembly of the wild relative of tea tree (Camellia taliensis) and comparative analysis with tea transcriptome identified putative genes associated with tea quality and stress response. BMC Genom. 2015;16(1):298. pmid:25881092
- 3. Duan ZF, Yang SM, Tang YC, Yi B, Li YY. Genetic diversity analysis of Camellia taliensis from Yunnan province. J Shanxi Agric Sci. 2019;47(12):2068–72.
- 4. Zhang WJ, Rong J, Wei CL, Gao LM, Chen JK. Domestication origin and spread of cultivated tea plants. Biodiversity Sci. 2018;26(4):357–72.
- 5. Min TL. A revision of Camellia Sect. Thea. Acta Botanica Yunnanica. 1992;2:115–32. https://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFQ&dbname=CJFD9697&filename=YOKE601.000
- 6. Min TL, Zhang WJ. The evolution and distribution of genus Camellia. Acta Botanica Yunnanica. 1996;(1). https://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFQ&dbname=CJFD9697&filename=YOKE601.000
- 7. Liu Y, Yang SX, Gao LZ. Comparative study on the chloroplast RPL32 -TRNL nucleotide variation with in and genetic differen tiation among ancient tea plan tations of Camellia sinensis var.assamica and C. taliensis (Theaceae) from Yunnan China. Acta Botanica Yunnanica. 2010;32(5):427–34.
- 8. Ogino A, Taniguchi F, Yoshida K, Matsumoto S, Fukuoka H, Nesumi A. A new DNA marker CafLess-TCS1 for selection of caffeine-less tea plants. Breed Sci. 2019;69(3):393–400. pmid:31598071
- 9. Mo X, Huang Y. Responses and resistance mechanisms of tea plants to stresses - a review. J Tea Sci. 2021;62(4):185–90.
- 10. Frankham R, Bradshaw CJA, Brook BW. Genetics in conservation management: Revised recommendations for the 50/500 rules, Red List criteria and population viability analyses. Biol Conserv. 2014;170:56–63.
- 11. Yang CR, Zhang YJ, Gao DF, Chen KK, Jiang HJ. Evaluation of germplasm resources of dali tea and the origin of cultivated large-leaf tea. J Tea Sci Technol. 2008;(3):1–4.
- 12. Ning GW, Yang SM, Song WX, Li YY, Tang YC, Zhao HY. Tea germplasm resources research in Yunnan for 60 years. J Plant Genet Resourc. 2023;24(3):587–98.
- 13. Huang LC, Chen HY, Luo YJ, Tao YL, Lan AQ. Study on genetic diversity of Camellia taliensis population in Lancang River Basin based on SSR markers. J Agric Biotechnol. 2025;33(1):68–78.
- 14. Huang R, Wang J-Y, Yao M-Z, Ma C-L, Chen L. Quantitative trait loci mapping for free amino acid content using an albino population and SNP markers provides insight into the genetic improvement of tea plants. Hortic Res. 2022;9. pmid:35040977
- 15. Qiao DH, Guo Y, Yang C, Li Y, Chen J, Chen ZW. Fingerprinting construction and genetic structure analysis of the main cultivated tea varieties in Guizhou Province. J Plant Genet Resourc. 2019;20(2):412–25.
- 16. Liu YC, Li JQ, Wei X, Yang YM, Zhang T, Wang XD. Genetic variation and structure analysis of different type blueberries (Vaccinium spp.) based on SLAF-seq technology. J Fruit Sci. 2023;40(8):1534–45.
- 17. Sun X, Liu D, Zhang X, Li W, Liu H, Hong W, et al. SLAF-seq: an efficient method of large-scale de novo SNP discovery and genotyping using high-throughput sequencing. PLoS One. 2013;8(3):e58700. pmid:23527008
- 18. Cheng L, Dong X, Liu Q, Wang R, Li Y, Huang X, et al. SLAF-Seq technology-based genome-wide association and population structure analyses of ancient Camellia sinensis (L.) Kuntze in Sandu County, China. Forests. 2022;13(11):1885.
- 19. Liu Y, Teng Y, Zheng J, Khan A, Li X, Tian Y, et al. Analysis of genetic diversity in tea plant population and construction of DNA fingerprint profile using SNP markers identified by SLAF-Seq. Horticulturae. 2025;11(5):529.
- 20. Feng J, Wang FT, Lin RM, Xu SC, Chen WQ. Research progress on genetics of wheat stripe rust resistance and distribution of resistant genes in inoculum source areas. J Plant Protec. 2022;49(1):263–75.
- 21.
Frankham R, Ballou J D, Briscoe D A. Introduction to conservation cenetics. Cambridge: Cambridge University Press; 2002. https://www.cambridge.org/core/books/introduction-to-conservation-genetics/F1F8EDB8B86A1790A406064296878B23
- 22. Zhu S, Niu E, Shi A, Mou B. Genetic Diversity Analysis of Olive Germplasm (Olea europaea L.) With Genotyping-by-Sequencing Technology. Front Genet. 2019;10:755. pmid:31497033
- 23.
Na DC. A study on genetic diversity of different geographic provenances of Larix gmelinii (Rupr.) Rupr and its utilization. Northeast Forestry University. 2005. https://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CDFD&dbname=CDFD9908&filename=2005136986.nh
- 24. Cornuet JM, Luikart G. Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data. Genetics. 1996;144(4):2001–14.
- 25. Wright S. The genetical structure of populations. Ann Eugen. 1951;15(4):323–54. pmid:24540312
- 26. Hewitt GM. Genetic consequences of climatic oscillations in the Quaternary. Philos Trans R Soc Lond B Biol Sci. 2004;359(1442):183–95; discussion 195. pmid:15101575
- 27. Hoban S, Archer FI, Bertola LD, Bragg JG, Breed MF, Bruford MW, et al. Global genetic diversity status and trends: towards a suite of Essential Biodiversity Variables (EBVs) for genetic composition. Biol Rev Camb Philos Soc. 2022;97(4):1511–38. pmid:35415952
- 28. Hazra A, Kumar R, Sengupta C, Das S. Genome-wide SNP discovery from Darjeeling tea cultivars - their functional impacts and application toward population structure and trait associations. Genomics. 2021;113(1 Pt 1):66–78. pmid:33276009
- 29. Wang J, Zhang Z, Gong Z, Liang Y, Ai X, Sang Z, et al. Analysis of the genetic structure and diversity of upland cotton groups in different planting areas based on SNP markers. Gene. 2022;809:146042. pmid:34715303
- 30. Jin FP, Zuo PX, Leng Y, Wu JJ, Xiong HY, Gao HT. Genetic diversity analysis of four populations of Schizothorax lantsangensis. Fisheries Sci. 2022;41(5):851–9.
- 31. Botstein D, White RL, Skolnick M, Davis RW. Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Hum Genet. 1980;32(3):314–31. pmid:6247908
- 32. Mao J, Jiang HJ, Yang RB, Li CX, Ma CY, Chen L, et al. Genetic diversity and population structure of wild and cultivated Camellia taliensis populations. J Tea Sci. 2021;41(4):454–62.
- 33. Huang DJ, Ma JQ, Chen L. SSR identification and pedigree analysis of PVP application cultivars in tea plant. J Tea Sci. 2016;36(1):68–76.
- 34. Liu BY, Sun XM, Li YY, Hunag PA, Wang YG, Cheng H. Analysis of genetic diversity and construction of DNA fingerprinting with EST-SSR markers for improved clonal tea cultivars in Yunnan Province. J Tea Sci. 2012;32(3):261–8.
- 35. Zhou M, Li YY, Sun XM, Wang JJ, Xie J, Cheng H. Genetic diversity assessment of ancient tea plants in Yunnan province of China revealed by EST-SSR markers. Acta Agric Boreali-Sinica. 2013;28(S1):91–6.
- 36. Ji PZ, Wang YG, Jiang HB, Tang YC, Wang PS, Zhang J. Genetic diversity of Camellia taliensis from Yunnan province of China revealed by AFLP analysis. J Tea Sci. 2009;29(5):329–35.
- 37. Zhao D-W, Yang J-B, Yang S-X, Kato K, Luo J-P. Genetic diversity and domestication origin of tea plant Camellia taliensis (Theaceae) as revealed by microsatellite markers. BMC Plant Biol. 2014;14:14. pmid:24405939
- 38. Varshney RK, Terauchi R, McCouch SR. Harvesting the promising fruits of genomics: applying genome sequencing technologies to crop breeding. PLoS Biol. 2014;12(6):e1001883. pmid:24914810
- 39. Hedrick PW, Garcia-Dorado A. Understanding inbreeding depression, purging, and genetic rescue. Trends Ecol Evol. 2016;31(12):940–52. pmid:27743611
- 40. Li MM, Kasun M, Yan LJ, Liu J, Gao LM. Genetic involvement of Camellia taliensis in the domestication of C. sinensis var. assamica (assimica tea) revealed by nuclear microsatellite markers. Plant Divers Resourc. 2015;37(1):29–37.
- 41. Li Y, Li YH, Yang QW, Zhang JP, Zhang JM, Qiu LJ. Genomics-based crop germplasm research: advances and perspectives. Sci Agric Sinica. 2015;48(17):3333–53.
- 42. Li L, Li X, Liu F, Zhao J, Zhang Y, Zheng W, et al. Preliminary investigation of essentially derived variety of tea tree and development of SNP markers. Plants (Basel). 2023;12(8):1643. pmid:37111866
- 43. Li L, Luo SC, Wang FQ, Li XR, Feng H, Shi YT. Genetic analysis and marker development for Wuyi tea (Camellia sinensis, Synonym: Thea bohea L.) based on GBS-SNP. J Tea Sci. 2023;43(3):310–24.
- 44. Chen L, Yu FL, Tong QQ. Discussions on phylogenetic classification and evolution of sect. Thea. J Tea Sci. 2000;(2):89–94.
- 45. Liu J, Möller M, Provan J, Gao L-M, Poudel RC, Li D-Z. Geological and ecological factors drive cryptic speciation of yews in a biodiversity hotspot. New Phytol. 2013;199(4):1093–108. pmid:23718262
- 46. Wei C, Yang H, Wang S, Zhao J, Liu C, Gao L, et al. Draft genome sequence of Camellia sinensis var. sinensis provides insights into the evolution of the tea genome and tea quality. Proc Natl Acad Sci U S A. 2018;115(18):E4151–8. pmid:29678829
- 47. Rellstab C, Gugerli F, Eckert AJ, Hancock AM, Holderegger R. A practical guide to environmental association analysis in landscape genomics. Mol Ecol. 2015;24(17):4348–70. pmid:26184487
- 48. Hoban S, Schlarbaum S. Optimal sampling of seeds from plant populations for ex-situ conservation of genetic biodiversity, considering realistic population structure. Biol Conserv. 2014;177:90–9.
- 49. Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol. 2013;79(17):5112–20. pmid:23793624
- 50. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25(14):1754–60. pmid:19451168
- 51. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The genome analysis toolkit: a mapreduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20(9):1297–303. pmid:20644199
- 52. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The sequence alignment/map format and SAMtools. Bioinformatics. 2009;25(16):2078–9. pmid:19505943
- 53. Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol. 2018;35(6):1547–9. pmid:29722887
- 54. Alexander DH, Novembre J, Lange K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 2009;19(9):1655–64. pmid:19648217
- 55. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38(8):904–9. pmid:16862161