1 Introduction

Tea (Camellia sinensis) is an important economic crop around the world. It also plays a special role in cultural exchange and health-related consumption. As the tea industry grows, interest in its genetic background has also increased. In recent years, there have been many advances in tea genome research. For example, high-quality reference genomes have been released, and pangenomes based on diverse tea resources have been built. These are major foundational breakthroughs. Kong et al. (2022) developed a pan-transcriptome dataset including 134 tea accessions. They identified 30,482 expressed genes. Among them, 4,940 genes came from de novo transcriptome assembly without a reference, and 5,506 were newly annotated based on the reference genome. These studies help us better understand the genetic diversity of tea plants. They have revealed more than 217,000 large structural variations (SVs) and around 56,000 presence/absence variations (PAVs), which have greatly enriched the genomic resources of tea (Xia et al., 2020; Tong et al., 2024; Tariq et al., 2024).

However, there are still many challenges. The tea genome is large and contains a high proportion of repetitive sequences. In particular, the presence of many LTR retrotransposons makes both genome assembly and annotation more difficult (Xia et al., 2020; Tariq et al., 2024). On top of that, the population structure of tea plants is quite complex. It is still hard to fully understand the genetic mechanisms behind key agronomic traits. In the past, researchers mainly used SNPs and small Indels for population studies and trait association analysis (Niu et al., 2019; Hazra et al., 2021). But now, more and more studies are shifting attention to SVs. These structural variants tend to affect larger genomic regions and often have stronger effects. Yet, they are usually overlooked in traditional analyses. 

SVs can cause large deletions, duplications, inversions, or even gene rearrangements. Many traits are closely linked to these changes, such as leaf shape, tea aroma, flavonoid biosynthesis, and cold resistance (Tong et al., 2024; Tariq et al., 2024). For instance, aroma-related pathways like terpenoid biosynthesis and phenylalanine metabolism are influenced by SVs and differentially expressed genes in purple tea flowers and leaves. Some structural genes, such as DAHPS and F3′5′H, are significantly upregulated in specific cultivars (Mei et al., 2021). Certain SVs are directly associated with trait differentiation. Traits like cold tolerance and tea quality show clear links to these variations, highlighting the dual role of SVs in both natural evolution and artificial domestication (Xia et al., 2020; Tong et al., 2024; Tariq et al., 2024).

This study summarizes current research on structural variations in tea plants. It focuses on methods for detecting SVs, strategies for integrating multi-omics data, and the application of SVs in breeding. Special attention is given to how SVs influence phenotype expression. The goal is to provide a systematic overview for genetic studies of tea. At the same time, it aims to offer theoretical support for molecular breeding and germplasm conservation.

2 Genome Structural Complexity of Tea Plants

2.1 Genome size and polyploidy in tea

The tea plant genome is large and structurally complex. It has been shaped by at least two whole-genome duplication (WGD) events. These events occurred roughly 30-40 million years ago and 90-100 million years ago. As a result of WGD and subsequent paralogous gene expansions, many gene families—especially those involved in secondary metabolite biosynthesis—have been enlarged. This expansion provides the genetic basis for the diversity of tea quality traits. Studies have also shown that WGDs contributed to the emergence and retention of lineage-specific genes. These genes play key roles in environmental stress responses and in determining the composition of tea aroma compounds (Zhao and Ma, 2021).

Repetitive sequences, particularly long terminal repeat retrotransposons (LTR-RTs), make up a significant portion of the tea genome. In some assembly versions, they account for as much as 70% of the genome. These transposable elements have driven genome expansion. By inserting preferentially into promoter regions and introns, they also influence gene expression and trait variation (Wei et al., 2018; Xia et al., 2020). With the help of long-read sequencing technologies, researchers have gained much better resolution in studying transposon distribution. Recent studies have revealed shared patterns of transposon organization across different tea genomes (Tariq et al., 2024).

2.2 Heterozygosity and genome plasticity

Cultivated tea resources show a high level of heterozygosity. This reflects their hybrid origin and rich genetic diversity. A study of 24 tea tree varieties showed that their heterozygosity (HS) ranged from 37.5% to 71.0%, with an average of 51.3%. Among them, the Fujian tea tree varieties had the highest heterozygosity, reaching 59.8%, which was much higher than Zhejiang (48.5%) and Yunnan (44.5%) (Tan et al., 2015). The heterozygosity is especially prominent in ancient landraces and hybrid wild types. Their genetic variation is much greater than that of pure wild species or modern cultivars (Niu et al., 2019; Hazra et al., 2021). This high genetic diversity forms the basis for the adaptability and trait variability seen in cultivated tea.

Wild and ancient tea populations also display clear structural dynamics. A large number of structural variations (SVs) and presence/absence variations (PAVs) have been found across populations from different geographic regions. These variations are often closely linked to important agronomic traits such as cold tolerance and leaf shape. Interestingly, they do not seem to have been strongly reduced by natural or artificial selection (Lu et al., 2021; Tong et al., 2024). The genetic structure of wild populations remains highly complex. This complexity continues to support ongoing diversification and adaptive evolution.

2.3 Implications for structural variation discovery

The tea plant genome contains a high proportion of repetitive sequences, shows clear signs of polyploidy, and has strong heterozygosity. These factors make it difficult to accurately detect structural variations. Traditional short-read sequencing technologies struggle to resolve complex regions, often resulting in incomplete or unclear identification of SVs (Samarina et al., 2022; Tariq et al., 2024).

To address these challenges, long-read sequencing and pangenome strategies have become essential tools. Long-read sequencing improves the resolution of repetitive and structurally complex regions. Meanwhile, constructing pangenomes helps distinguish between core and variable genes, allowing for a more complete view of structural diversity across tea accessions. These approaches are not only useful for identifying trait-related structural variations, but also offer strong support for future studies in tea functional genomics and molecular breeding (Tong et al., 2024; Tariq et al., 2024).

3 Structural Variations in the Tea Genome

3.1 Characteristics of the Camellia sinensis genome

Tea plants (Camellia sinensis) mainly include two cultivated varieties: the small-leaf type (var. sinensis, CSS) and the large-leaf type (var. assamica, CSA). Whole-genome resequencing of 30 cultivated varieties and 3 wild accessions by An et al. (2020) revealed 6,440,419 unique mutations in CSS and 6,176,510 in CSA, indicating clear genomic divergence between the two groups (Figure 1). The CSS subgroup shows higher genetic diversity, while CSA carries more nonsynonymous mutations. This pattern may reflect the effects of balancing selection. Further analysis showed that CSS is mainly associated with traits like cold tolerance and aroma biosynthesis. In contrast, CSA is more linked to leaf development and the synthesis of flavonoids and alkaloids. Huang et al. (2022) found that in CSA cultivars, the expression of CsAN1—a key transcription factor for anthocyanin biosynthesis—is significantly higher, especially in the anthocyanin-rich variety ‘Zijuan’. A deletion mutation in this gene led to the loss of anthocyanin synthesis in some F₁ individuals. During the domestication of each group, specific trait-related genes and selective signatures were retained, reflecting adaptations to different environments and uses (Tong et al., 2024; Duan et al., 2024).

In the tea genome, large-scale structural variations (SVs) and presence/absence variations (PAVs) are not evenly distributed. Instead, they tend to cluster in specific regions or "hotspots". These areas often harbor genes related to agronomic traits, such as stress resistance and quality-related genes, forming the genetic foundation for functional diversity across tea germplasms (Tong et al., 2024; Tariq et al., 2024).

3.2 Identified SVs in cultivated and wild tea accessions

A large number of insertion and deletion variations (indels) have been identified across different cultivated tea varieties. So far, more than 217,000 large structural variations (SVs) and over 56,000 presence/absence variations (PAVs) have been detected. Some of these are directly linked to key traits, such as cold tolerance, and help explain phenotypic differences between CSS and CSA (Tong et al., 2024). Copy number variations (CNVs) are widespread in wild and ancient tea populations. These affect many gene families involved in secondary metabolism and stress responses. Such variations not only enrich the functional genome of tea plants but also provide a genetic basis for the broad adaptability and trait diversity seen in wild resources (Lu et al., 2021; Tariq et al., 2024).

In wild and ancient tea accessions, many chromosomal structural changes, such as inversions and translocations, have also been observed. These SVs are strongly associated with adaptive traits like leaf shape and plant architecture. Despite natural or artificial selection pressures, these structures have remained intact, suggesting their crucial role in the evolutionary history of tea (Tong et al., 2024).

3.3 Evolutionary implications of SVs in tea

Structural variations have played a key role in the domestication of tea plants. They helped shape population structure and drove the divergence between CSS and CSA. Some SVs are linked to important domestication traits, such as leaf development, metabolite biosynthesis, and stress tolerance. These variations have contributed to the selection and fixation of functional genes (Duan et al., 2024; Tong et al., 2024).

Many SVs and PAVs can serve as genetic markers of both natural and artificial selection. The genomic regions where they are located often reflect selection under specific environmental pressures or human cultivation preferences. These variations are closely associated with a wide range of agronomic and quality-related traits, highlighting their important role in the ongoing evolution and breeding improvement of tea plants (Lu et al., 2021; Tong et al., 2024).

4 Functional Roles of Structural Variations

4.1 Gene expression changes driven by SVs

Structural variations (SVs), such as insertions and deletions, often occur in regulatory regions like promoters and enhancers. These changes can alter gene expression levels. In the high-quality reference genome of tea, studies have shown that about 70.38% of the genome consists of long terminal repeat retrotransposons (LTR-RTs). These LTR-RTs tend to insert near promoters and introns, playing a key role in diversifying gene expression. They particularly affect genes related to tea aroma—such as those involved in terpene biosynthesis—and stress resistance (Xia et al., 2020). Therefore, SVs can regulate the expression of important functional genes and contribute to quality traits and environmental adaptability.

SVs can also rearrange genomic regions, introducing new regulatory elements or forming chimeric gene structures. This may lead to the creation of fusion genes or novel transcripts. Tong et al. (2024) resequenced 363 tea accessions from around the world and constructed a population structure map covering eight subgroups. They identified 730 Mb of new sequences—regions not annotated in existing reference genomes—and discovered 6,058 full-length protein-coding new genes. In addition, they detected 217,376 large SVs and 56,583 PAVs. These findings suggest that SVs help shape transcriptomic diversity and may drive the emergence of new functional genes, promoting trait differentiation and evolutionary change.

4.2 SV-mediated gene family evolution

Structural variations, especially gene duplications and presence/absence variations (PAVs), have promoted the expansion of several secondary metabolism-related gene families in tea plants. For example, genes involved in the biosynthesis of tea polyphenols—such as catechins—as well as theanine and caffeine, have been shown to undergo significant amplification through SVs. These compounds not only shape tea quality but are also closely linked to its health benefits (Wei et al., 2018). In recent years, tandem duplications have further increased the number of genes related to aroma biosynthesis and stress resistance. These genes are often clustered together, forming functional modules (Xia et al., 2020).

At the same time, some gene families have contracted due to SVs. For instance, disease resistance gene clusters may have shrunk under the selective pressures of domestication and environmental adaptation. This dynamic restructuring of gene families influences how tea plants respond to both biotic and abiotic stresses (Xia et al., 2020; Tong et al., 2024).

5 Structural Variations and Trait Diversity

5.1 Metabolic traits and tea quality

Structural variations (SVs), including large-scale insertions, deletions, and copy number changes, are prevalent in genes involved in flavonoid and catechin biosynthesis. These SVs have contributed to the expansion and transcriptional divergence of gene families such as acyltransferases and leucoanthocyanidin reductases, which are critical for the accumulation of monomeric galloylated catechins—a key determinant of tea quality (Wei et al., 2018; Tong et al., 2024). Domestication signatures in Camellia sinensis var. assamica (CSA) are particularly enriched in flavonoid and alkaloid biosynthesis genes, highlighting the role of SVs in metabolic trait diversity (Tong et al., 2024).

SVs, especially tandem duplications and presence/absence variations (PAVs), have amplified genes related to aroma compound biosynthesis and theanine production. In Camellia sinensis var. sinensis (CSS), SVs are associated with genes involved in amino acid metabolism and aroma, directly impacting the sensory qualities and health benefits of tea (Wei et al., 2018; Xia et al., 2020; Tong et al., 2024). Functional divergence of the glutamine synthetase gene family, driven by SVs, has led to the evolution of theanine synthetase, a key enzyme for theanine accumulation (Wei et al., 2018).

5.2 Abiotic and biotic stress responses

SVs and PAVs are linked to stress response traits, including drought and cold tolerance. For example, specific PAV genes (CSS0049975 and CSS0006599) have been experimentally shown to drive cold tolerance differences between CSA and CSS (Tong et al., 2024). The expansion of stress resistance gene clusters through SVs further enhances the adaptability of tea plants to diverse environments (Xia et al., 2020).

SVs also affect disease resistance loci, contributing to the contraction or expansion of resistance gene clusters. These changes influence the plant’s ability to respond to biotic stresses and are important for breeding disease-resistant cultivars (Xia et al., 2020; Tong et al., 2024). The pangenome approach has revealed dispensable genes related to disease resistance, underscoring the functional impact of SVs on plant health (Tariq et al., 2024).

5.3 Morphological and developmental traits

Genome-wide association studies (GWAS) and selection signal analyses have shown that many structural variations (SVs) are significantly associated with morphological traits such as leaf size, shape, and hair density in both ancient and cultivated tea varieties (Lu et al., 2021; Tong et al., 2024). In a study of 415 tea accessions from Guizhou, researchers used GBS technology to obtain 30,282 high-quality SNP markers and performed GWAS analysis. They identified nine SNPs significantly associated with leaf length (MLL), leaf width (MLW), leaf area (MLA), and leaf shape index (MLSI) (P < 1.655×10⁻⁶). These markers were widely distributed across different genetic backgrounds (Niu et al., 2020). Similarly, Zhang et al. (2022) conducted a GWAS using SLAF-seq on 123 tea samples from southern Guizhou. They identified 11 candidate genes linked to leaf tip shape and seven associated with overall leaf form. Some leaf development-related genes showed clear differences in allele frequency across production regions. These structural variations offer a genetic basis for the phenotypic diversity observed among different tea germplasms.

SVs also contribute to regulating branching patterns and flowering time in tea plants. Several candidate genes have been identified as related to plant architecture and developmental stages (Lu et al., 2021). For example, Xia et al. (2021) found that the CsLAZY1 gene plays a central role in controlling branch gravitropism and branching angle. CsLAZY1 is mainly expressed in stem tissues and is localized on the plasma membrane. When introduced into Arabidopsis, it enhanced the plant's gravitropic response, indicating that this gene is involved in the regulation of branch orientation and affects the overall shoot structure of tea plants. The continued presence of such structural variations in wild and ancient populations suggests their lasting role in adaptive evolution and trait differentiation.

6 Case Studies

6.1 Structural variations in ancient tea genomes

Ancient tea trees distributed across Southwest China are valuable materials for studying the evolution and domestication of tea plants. Lu et al. (2021) conducted whole-genome resequencing of 120 ancient tea individuals and identified over 410 million SNPs and nearly 19 million InDels. Many of these were nonsynonymous mutations and frameshift indels, indicating a high level of structural variation within the genomes of ancient tea trees. These variants were widely distributed across both coding and regulatory regions. The dN/dS ratio was close to 1, suggesting that strong genetic diversity has been maintained under natural selection.

Population structure analysis revealed that the samples clustered into three main groups, which were further divided into seven subgroups. This pattern reflects genetic divergence driven by geographic isolation. Through genome-wide association studies (GWAS), researchers identified several candidate genes associated with important traits. Multiple nonsynonymous mutations were found to be significantly related to leaf color, tooth density, tooth depth, and plant type. For example, TEA012477 and TEA029928 were shown to influence chlorophyll synthesis and plant morphology, respectively (Figure 2). The study also highlighted differences in linkage disequilibrium (LD) decay rates among populations, suggesting that the accumulation of structural variations varies across groups. These findings provide strong evidence for the connection between structural genome variation and phenotypic diversity in tea.

6.2 SVs Related to catechin and theanine biosynthesis

Catechins and theanine are key compounds that determine both the flavor and health benefits of tea. Wei et al. (2018) used the cultivated tea variety Camellia sinensis var. sinensis (CSS) to build a high-quality draft genome, laying the groundwork for exploring the molecular basis of tea quality. Their study revealed that the CSS genome underwent two rounds of whole-genome duplication (WGD), which occurred around 30-40 million years ago and 90-100 million years ago. These events greatly increased the copy number of metabolic genes. Extensive tandem duplications led to species-specific expansion of the SCPL1A family of acyltransferases. Many of these genes are highly expressed in young buds and leaves and are strongly correlated with high levels of monomeric catechins.

Another key structural variation involves the origin of the CsTSI gene. This gene evolved through functional divergence from the GSI-type glutamine synthetase family and acquired the ability to synthesize theanine (Figure 3). Its function has been validated in transgenic Arabidopsis, confirming that the new function brought by this structural change contributed to the formation of a tea-specific metabolic pathway. The study also found clear structural differences between the genomes of CSS and CSA, including disrupted collinearity and partial gene rearrangements. These findings further support the central role of structural variations in the evolutionary trajectory of tea plants.

7 Technological Advances and Applications

7.1 Progress in SV detection technologies

The introduction of third-generation sequencing technologies—especially the widespread application of long-read sequencing—has significantly improved the accuracy of structural variation (SV) detection in the tea genome (Qiao et al., 2024). These platforms allow for high-quality genome assembly and enable the identification of large insertions, deletions, and presence/absence variations (PAVs), many of which are difficult to detect using traditional short-read sequencing methods (Xia et al., 2020; Tariq et al., 2024). Long-read technologies also excel at resolving repetitive sequences and transposon insertions, which are abundant in the tea genome (Tariq et al., 2024).

The construction of the tea pangenome integrates multiple high-quality genome assemblies. This approach has allowed researchers to comprehensively catalog SVs across different tea resources. It covers both core and variable genes and reveals the functional impacts of structural variations on traits such as flavor, stress tolerance, and disease resistance (Tariq et al., 2024). The establishment of the tea pangenome has greatly advanced the identification of novel sequences and gene-centric variations. It provides a valuable genetic foundation for trait association studies and molecular breeding (Tong et al., 2024; Tariq et al., 2024).

7.2 Multi-omics integration with SV datasets

Integrating transcriptomic data with SV datasets enables the validation of SV impacts on gene expression. For example, SVs affecting promoter regions or gene copy number have been linked to transcriptional changes in genes involved in catechin biosynthesis and stress responses, supporting their functional relevance in trait diversity (Wei et al., 2018; Tong et al., 2024).

Metabolomic analyses, combined with genomic and transcriptomic data, provide insights into how SVs influence metabolic pathways. Studies have shown that SV-driven gene family expansions and transcriptional divergence are associated with the accumulation of key metabolites, such as catechins and theanine, which are central to tea quality and health benefits (Wei et al., 2018).

7.3 Application in tea breeding and improvement

Structural variations (SVs) and high-impact mutations identified through advanced sequencing and pangenome analysis have become important molecular markers in tea breeding. SVs and SNPs associated with agronomic and biochemical traits have been successfully used to develop markers that support the application of marker-assisted selection (MAS) in tea improvement programs (Hazra et al., 2021).

Genomic selection strategies that incorporate SV information can improve the prediction accuracy of complex traits and accelerate the breeding of superior tea cultivars. Using 1,421 DArTseq markers, researchers developed a multi-model prediction framework targeting drought resistance and quality traits. Among the models, those integrating KEGG pathway and protein annotation data performed best. Notably, the extreme learning machine (ELM) model showed the highest accuracy in predicting catechin content, astringency, and leaf color (Koech et al., 2019). Integrating SV data with genome-wide association studies (GWAS) and multi-omics approaches can help pinpoint key candidate genes. This strategy facilitates the development of new tea varieties with desirable traits such as high quality, stress tolerance, and disease resistance (Lu et al., 2021; Tong et al., 2024; Tariq et al., 2024).

8 Concluding Remarks

Structural variations (SVs), including large-scale insertions, deletions, presence/absence variations (PAVs), and copy number changes, are abundant in the tea genome. Over 217,000 SVs and more than 56,000 PAVs have been identified across diverse tea accessions, significantly expanding the gene pool and contributing to the remarkable genetic and functional diversity observed in tea plants. SVs are unevenly distributed and often cluster in regions associated with key agronomic and adaptive traits.

SVs play a vital role in shaping important tea traits, including metabolic pathways (flavonoid, catechin, and theanine biosynthesis), stress responses (cold and drought tolerance), and morphological features (leaf size, shape, and plant architecture). Many SVs are linked to domestication and adaptation, with subspecies-specific patterns observed between C. sinensis var. sinensis and var. assamica.

Despite the identification of numerous SVs, only a small subset has been functionally validated for their direct impact on gene expression and phenotypic traits. Most associations remain correlative, and experimental evidence for causality is limited. Although recent studies have expanded the number of sequenced accessions, population-scale SV data remain insufficient, especially for wild and underrepresented tea populations. This limits the ability to fully capture the spectrum of SV diversity and its effects on trait variation.

Future research should focus on high-resolution mapping of SVs using advanced sequencing and pangenome approaches, coupled with functional genomics and gene editing to validate the roles of specific SVs in trait determination. Integrating transcriptomic and metabolomic data will further clarify the molecular mechanisms underlying SV-driven trait diversity. Incorporating SV information into breeding programs through marker development and genomic selection will accelerate the improvement of tea cultivars for quality, stress tolerance, and adaptation. The development of comprehensive SV-based resources will support precision breeding and the conservation of tea genetic diversity.

Acknowledgments

The authors sincerely thank Mr. Li for reviewing the manuscript and providing valuable suggestions, which contributed to its improvement. Additionally, heartfelt gratitude is extended to the two anonymous peer reviewers for their comprehensive evaluation of the manuscript. 

Conflict of Interest Disclosure

The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.

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