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Comparative and evolutionary analysis of chloroplast genomes from five rare Styrax species

BMC Genomics volume 26, Article number: 450 (2025) Cite this article

Abstract

Background

Styrax, a vital raw material for shipbuilding, construction, perfumes, and drugs, represents the largest and most diverse genus in the Styracaceae. However, there is a relative scarcity of research on Styrax, particularly in evolution and genetics. Therefore, this study conducted comparative and evolutionary analyses of the chloroplast genomes of five rare Styrax species (S. argentifolius, S. buchananii, S. chrysocarpus, S. finlaysonianus, and S. rhytidocarpus).

Results

The results indicated that, despite high levels of conservation in chloroplast genome structure among these species, specific mutation hotspot regions exist, particularly involving the expansion and contraction of the IR region. Additionally, evidence of positive selection was detected in eight genes (atpB, ccsA, ndhD, petA, rbcL, rpoC1, ycf1, and ycf2), which may be associated with adaptive evolution in response to environmental changes. Phylogenetic analysis revealed conflicts between trees constructed based on coding sequences and complete chloroplast genomes for several species, which were similar to previous phylogenetic studies.

Conclusion

This study underscores the importance of increasing sample sizes to enhance the accuracy of phylogenetic analyses and provides a new perspective on understanding the adaptive evolution of Styrax species. These findings are not only important for the conservation and sustainable use of Styrax, but also provide valuable insights for research in plant evolution and ecology within the genus.

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Background

The chloroplast in green plants plays a vital role in the process of photosynthesis and energy provision [1], as well as actively participating in the biosynthesis of amino acids, fatty acids, vitamins, and pigments [2]. The structure of chloroplast genomes is characterized by a circular quadripartite organization, which includes two inverted repeat regions (IRs), a small single copy (SSC) region, and a large single copy (LSC) region that is greatly conserved [3]. In addition, chloroplast genes exhibit a relatively high degree of conservative and play a crucial role in essential biological processes such as photosynthesis, transcription, and translation [4]. The length of these sequences varies among different species, typically ranging from 120 to 160 kb [5]. Notably, this includes two sets of four ribosomal RNA genes and 30 tRNA genes that possess the remarkable ability to interact with all mRNA codons through subtle conformational adjustments [6, 7]. In angiosperms, the maternal inheritance of the chloroplast genome helps maintain the stability of species evolution [8]. However, the occurrence of mutational events provides valuable information for evolutionary research [9], population classification [10, 11], and serves as effective genetic markers to unravel intricate evolutionary processes [12]. Consequently, chloroplast genes present an ideal research subject for investigating species evolution [13].

The diversity of chloroplast genomes provides an abundant source of specific markers for elucidating phylogenetic relationships at various levels [14,15,16]. Additionally, due to the maternal inheritance of chloroplasts in most angiosperms [17], their divergence from nuclear phylogenetic relationships can offer valuable insights into speciation processes such as hybridization and incomplete lineage sorting [18, 19]. Therefore, the comparative analysis of chloroplast genomes holds significant potential for investigating plant evolution. The modification of gene content in the chloroplast genome can facilitate species’ adaptation to specific habitats and life strategies [20, 21]. Environmental changes and variations in habitats may exert selective genetic pressure, thereby leaving a trace of natural selection in genes associated with environmental adaptation. Genes that undergo positive selection typically enhance individual fitness and reproductive capacity [22]. Consequently, the identification of selection pressure and adaptive evolution of genes has emerged as a prominent research area in molecular, forming the foundation for germplasm resource studies.

As a particularly important genus, Styrax L. encompasses approximately 130 species and represents the most diverse, extensively distributed, and highly distinct category within Styracaceae [23]. Ser. Cyrta in Styrax, for instance, is found in temperate lowlands and tropical montane forests in eastern and southeastern Asia as well as North America. The average annual precipitation ranges from 80 to 300 cm with no prolonged dry season [24, 25]. Due to its aromatic properties and wood characteristics, Styrax can be utilized as a raw material for shipbuilding, construction, perfume, cosmetics, and pharmaceuticals [25, 26]. Furthermore, the seed oil or resin of several Styrax species is a valuable medicinal ingredient and raw material for the manufacture of aromatic oils [27].

The classification of Styrax based on morphological characteristics has been a subject of considerable controversy throughout history, largely due to the significant impact of environmental factors on the morphological changes observed in the various species. At present, the majority of research on Styrax is centered on the sequencing, assembly, and construction of phylogenetic relationships of chloroplast genomes, most of which pertain to individual species [28,29,30,31]. Fritsch conducted a morphological phylogenetic analysis of Styrax and made revisions to the taxonomy of interspecific relationships within the genus [32]. He divided Styrax into Sect. Styrax (ca. 33 species) and Sect. Valvatae (ca. 97 species), while also dividing Sect. Styrax into Ser. Styrax and Ser. Cyrta, Sect. Valvatae is divided into Ser. Valvatae and Ser. Benzoin. By utilizing several chloroplast sequences (ndhF-rpl32-trnL, trnL-trnF, trnS-trnG, and trnV-ndhC) as well as nrDNA internal transcribed spacer (ITS), Fritsch and Morton successfully establish a robust phylogenetic relationship that supports Styrax as a monophyletic group [24]. Furthermore, they classify the South American dioecious branch into two distinct sublines: Styrax subseries Latifoli and Foveolaria [33]. Additionally, Song et al. employ DNA polymorphism analysis to identify ycf1b and trnT-trnL as specific DNA barcodes for Styrax in order to elucidate intergeneric and interspecific relationships with greater precision [5]. The currently available samples of chloroplast genomes only represent a quarter of the entire genus, and there is a lack of research on rare species. Debates among scholars regarding the synonymization and segregation of species names have been ongoing in the study of taxonomy and systematics [25, 34]. For example, S. japonicus has a wide distribution and diverse morphological characteristics, making it one of the most heterogeneous species in Styrax. Although S. grandiflorus is currently used as a synonym for S. japonicus, phylogenetic analysis of the chloroplast genome suggests that S. japonicus and S. grandiflorus are positioned in separate branches and exhibit distinct morphologies from each other [5, 28].

While current research has offered some insights into Styrax, the understanding of its adaptive evolution remains limited in the field. Therefore, it is crucial to further investigate the adaptive evolution and diversity of its chloroplast genome to enhance our comprehension. As a result, in this study, we conducted sequencing and analysis on five Styrax species while incorporating additional data from NCBI for a comprehensive examination. Specifically, our objectives are to (1) analyze the distinct characteristics of Styrax and genes associated with adaptive evolution, (2) reconstruct and compare phylogenetic relationships, and (3) explore potential patterns of adaptive evolution in Styrax by examining its associated chloroplast genes and phylogeny.

Result

Assembly and annotation of the Styrax chloroplast genome

In this study, the assembly of five chloroplast genomes revealed a typical quadripartite structure, consisting of one LSC region, one SSC region, and a pair of IR regions. The genome sizes ranged from 157,817 bp to 158,015 bp with GC content ranging from 36.9 to 37% (Supplement Table 1). Subsequently, it was observed that the five species each contained eight rRNA, 37 tRNA, and 87 protein-coding genes. Additionally, the clpP, rps12, and ycf3 gene harbors two introns. All genes can be categorized into three types: (1) Photosynthesis; (2) self-replication; and (3) others (Supplement Table 2).

Analysis of the Chloroplast genome structure of Styrax

By utilizing OGDRAW for the visualization of chloroplast genomes among multiple species, it was observed that there existed a remarkable similarity in genome structure across various Styrax species (Supplement Fig. 1). Through SSR analysis, the Styrax chloroplast genome was found to contain a total of SSRs, with the majority (72.41–81.36%) located in the LSC region. The IR regions contained between 3.33 and 5.17% of SSR loci, while the SSC region included between 11.86 and 17.24% (Fig. 1A). The statistical analysis of SSR markers across five species highlighted that the A/T repeat type was particularly abundant, with all five species exhibiting a relatively high number of SSR markers in this category. Notably, S. argentifolius, S. finlaysonianus, and S. rhytidocarpus each possessed one SSR marker for the AAT/ATT repeat type. Additionally, both S. argentifolius and S. finlaysonianus were found to have one SSR marker for the ATC/ATG repeat type. In contrast, S. chrysocarpus uniquely exhibited one SSR marker for the AT/AT repeat type (Fig. 1B). There were 50 repeats in these five species, which included complementary, forward, palindromic, and reverse repeats. In general, the proportion of palindromic sequences is highest among the five species. The number of repetitive types in S. argentifolius and S. chrysocarpus is similar, while that in S. buchananii, S. finlaysonianus and S. rhytidocarpus is comparable. (Fig. 1C).

Fig. 1
figure 1

Analysis of SSR sites and repetitive sequences in five chloroplast genomes. (A). Distribution of SSRs in the five samples; (B). Number of different SSRs loci types; (C). Number of different repeat types. Note: In (A), symbol (+) represented the position of SSRs, and the proportion of text displayed; In (C), C: complementary repeats, F: forward repeats, P: palindromic repeats, R: reverse repeats

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The complete chloroplast genome of Styrax was analyzed using the reference chloroplast genome of S. japonicus in mVISTA (Supplement Fig. 1), revealing a significant level of similarity and conservation among the chloroplast genomes within the genus Styrax. Notably, coding regions exhibited higher levels of conservation compared to non-coding regions, while the IR regions demonstrated lower variability than the LSC and SSC regions. Additionally, the IR region of these five species exhibited varying degrees of expansion and contraction when compared to other closely related species (Fig. 2). The rps19 was located at LSC-IRB junction, ndhF and ycf1 were located at the SSC-IR junction, trnH was located at IRA-LSC junction. Notably, rpl2 was found to be significantly closer to the IR-LSC boundary within S. argentifolius and S. finlaysonianus, and trnH was found to have shifted entirely into the LSC region due to the contraction of the IR region.

Fig. 2
figure 2

Comparison of chloroplast genome structure in five species and five closely related species. IR (Inverted repeat), LSC (Large single copy) and SSC (Small single copy) regions and border genes are indicated. Note: JLA: junction between LSC and IRa; JLB: junction between LSC and IRb; JSA: junction between SSC and IRa; JSB: junction between SSC and IRb

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Codon bias analysis and selective pressures in the evolution

The examination of five chloroplast genomes demonstrated that the GC and GC3s composition within the codons was consistently lower than 0.5, suggesting a predilection towards A/T bases and A/T-ending codons in Styrax chloroplast genomes. The synonymous codon usage (RSCU) values showed similarity across the five Styrax chloroplast genomes (Fig. 3A). A total of 37 codons exhibited an RSCU value greater than 1 (Fig. 3B), with only one of these codons ending in G (UUG). Among the codons with an RSCU value less than 1, except for UGA and CUA, which terminate in A, the remaining codons conclude with either C or G.

Since some genes had Ks values of 0, resulting in an invalid Ka/Ks ratio. Of the 80 common genes, only 42 genes were included in the Ka/Ks analysis (Fig. 3C). The result suggested that 8 genes (atpB, ccsA, ndhD, petA, rbcL, rpoC1, ycf1, and ycf2) possessed Ka/Ks ratios > 1 in at least one pairwise comparison among the five species.

Fig. 3
figure 3

Relative synonymous codon usage and selective pressures in the evolution. (A). Codon content of 20 amino acids and stop codons in all protein-coding genes of five chloroplast genome; (B). Distribution of codon preference in five species; (C). Ka/Ks values of protein-coding genes of the five comparative combinations. Note: in (A), the top panels show the RSCU for the corresponding amino acids, and the colored blocks shown below represent different codons; In (C). Ka: nonsynonymous; Ks: synonymous

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Nucleic acid polymorphism analysis

In the analysis of Pi value in protein-coding sequences (Fig. 4A) and complete chloroplast genome sequences (Fig. 4B), the findings revealed varying levels of divergence across these three databases. The Pi values of ndhF, psbI, rbcL, rps8, rps19, and ycf1 among the 80 protein-coding sequences were observed to exceed 0.07. In intergenic regions, four fragments (accD-psaI, petA-psbJ, psbJ-psbL, rps16-trnQ) were detected with high Pi values. Moreover, the analysis of the entire chloroplast genome revealed a higher level of conservation in the IR region compared to the SC region.

Fig. 4
figure 4

Nucleotide diversity of chloroplast genomes in five Styrax species. (A). Pi in CDS; (B). chloroplast genome Pi value. Note: window length: 600 bp, step length: 50 bp; X axis: position of the midpoint of each window; Y axis: Pi of each window. The blue line represents the trajectory of the value of Pi

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Phylogenetic analysis

ModelFinder determines that the optimal model for both ML and BI methods is GTR + G. The topology based on CDS sequences and complete chloroplast genomes shows similarity, with reduced internal branches in Styrax indicating low differentiation (Fig. 5).

In ML tree, S. chrysocarpus and S. buchananii each form individual clades, but formed a single clade in the CDS tree. Also, in ML, S. finlaysonianus and S. agrestis composed into a sub-branch and form a monophyletic group with S. rhytidocarpus, S. hunans, S. roseus, and S. faberi. However, in the CDS tree, it was observed that S. finlaysonianus and S. rhytidocarpus clustered into a subclade and formed a monophyletic group with S. hunans, S. roseus, and S.agrestis. Furthermore, the position of S. argentifolius did not change between the two methods. Moreover, apart from the five species mentioned in this study, there are instances of lower support rates for certain species in these two phylogenetic trees, such as S. dasyanthus, S. calvescens, and S. confusus, among others.

In general, the four remaining species, except for S. argentifolius, exhibited varying degrees of phylogenetic conflict in both analyses. This conflict was observed not only within these four species but also in S. faberi, S. japonicus, and S. grandiflorus.

Fig. 5
figure 5

Phylogenetic tree analysis using Maximum Likelihood (ML) and Bayesian inference (BI) based on complete chloroplast genomes and CDS sequences. (A) Complete chloroplast genomes with ML method analysis. (B) CDS sequences with BI method analysis. Note: the blue circle at the branch node signifies the support rate of employing the bootstrap method, with its area directly proportional to the degree of support

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Discussion

In this study, we assembled chloroplast genomes of five rare Styrax species and furtherly performed comparative and evolution analyses. The results indicate that despite a high degree of similarity in their chloroplast genome structure, there are still discernible mutation hotspots. Specifically, (1)The results of the SSR analysis of the chloroplast genome indicated polymorphism; (2) the IR region of the chloroplasts in the five species exhibited varying degrees of expansion or contraction; (3) Evolutionary analysis revealed positive selection in eight genes; (4) Phylogenetic trees based on CDS and complete chloroplast genomes displayed multiple conflicts in relationship inference. Therefore, we will discuss the aforementioned four points.

Fluctuations of SSR in Styrax chloroplast genome

As a highly polymorphic marker, SSR holds significant application value in plant taxonomy and germplasm identification [35]. Compared with other markers, SSR possesses the characteristics of high polymorphism and ease of detection, being particularly suitable for differentiating closely related species [36,37,38]. In chloroplast genomes, the number of SSR motifs varies even in the same genotype due to changes in tandem arrays of SSR motifs [39].

In this study, the majority of SSR were identified within the LSC region of the chloroplast genome, predominantly as single nucleotide repeats. Notably, Zheng et al. reported that SSR in the LSC region of Styrax japonicus Siebold & Zucc. accounted for 77.59–79.66% [40]. Utilizing the same MISA parameter settings, our analysis revealed that the proportion of SSR in the five rare species ranged from 72.41 to 81.36%, with similar fluctuations observed in the SSC and IR regions. Research conducted by Morgante et al. indicates that SSR locus tend to be more common in the non-repetitive DNA regions of plant genomes [41], which may explain the variability in SSR proportions within the LSC and SSC regions of the Styrax chloroplast genome. Furthermore, the locus of SSRs exhibits significant dynamic changes, particularly in intergenic and non-coding regions, reflecting both genomic evolution and functional regulation [42]. Previous studies have demonstrated that SSR polymorphism can influence an organism’s adaptability to environmental changes [43]. Therefore, we hypothesize that the fluctuation in SSR ratios across the LSC, SSC, and IR regions in our five species may represent an evolutionary adaptation of chloroplast genomes to diverse habitats, potentially contributing to the survival and proliferation of Styrax in varied ecosystems.

In summary, SSR analysis offers more comprehensive data support for comparative genomics research. Furthermore, the utilization of SSR markers in gene mapping and breeding programs is expected to expand significantly, particularly in marker-assisted selection and genome editing. Importantly, SSR analysis will facilitate a deeper understanding of genomic dynamics and its role in evolution and adaptation, thereby providing a scientific foundation for biodiversity conservation and sustainable use.

Expansion and contraction of IR region

The findings of this study suggest that the boundary genes of five rare Styrax species appear to be consistently maintained with no significant alterations. However, it was observed that the rps19 and trnH of S. argentifolius and S. finialysonlanus have fully encroached into the LSC region, indicating a contraction of the IR region. Furthermore, the length of the IR region in S. buchananii is larger than that of other species, while the LSC region is slightly shorter, reflecting an expansion of the IR region.

The expansion or contraction of IR regions in the chloroplast genome is typically attributed to various factors such as genome rearrangement [44], random mutations [45], evolutionary pressure [46], and gene transfer [47]. While the IR region is generally considered highly conserved [48], variations in boundary genes can result in gene loss or pseudogene formation, a common phenomenon in chloroplast genome evolution that significantly impacts its length [49].

The IR region of the chloroplast genome is generally considered to be the most stable, and its expansion can enhance the genetic stability of the entire genome [50]. Conversely, contraction of the IR region may lead to increased genetic diversity in the overall genome. Additionally, current studies have demonstrated that the expansion or contraction of the IR region influences gene dose, which subsequently affects gene expression. For instance, the IR region encompasses ribosomal RNA operons, and its expansion can raise the dose of rRNA genes, thereby enhancing the biosynthetic capacity of the ribosome and improving the expression efficiency of genes related to photosynthesis [48]. In tobacco, the removal of the IR region led to a slight reduction in the number of ribosomes, suggesting that the gene dosing effect of the IR region has a significant impact on ribosome biosynthesis [51].

Studies on the chloroplast genome of Gentianinae (Gentianaceae) indicate that the varying degrees of contraction and expansion of IR regions in multiple species of Gentianinae might be caused by gene loss and duplication. Meanwhile, the study revealed that microstructural changes in the genome and gene loss are associated with alterations in selection pressure [52, 53]. For instance, the loss of the ndh gene complex could be related to changes in environmental stress, such as variations in temperature, light, and moisture conditions. In some plants adapted to drought or bright light environments, the loss of ndh genes might be an adaptive evolution [54]. Thus, we hypothesize that changes in the IR region influence the function of the chloroplast genome to a certain extent, leading to adaptation to specific environmental climates to enhance the reproduction and regeneration of species.

In this study, both contraction and expansion were observed in the chloroplast genomes of five rare species at Styrax, indicating dynamic changes in their genomes. Such dynamic variations are often evolutionary responses to environmental pressures and adaptive evolution aimed at improving species’ ability to adapt. In summary, the expansion and contraction of the IR region have significant impacts on plant survival and reproduction by influencing gene dose, genome stability, and gene expression. These alterations not only assist plants in adapting to diverse environmental conditions but might also offer a selective advantage during evolution.

Positive selection of eight genes

In this investigation, a total of eight genes (atpB, ccsA, ndhD, petA, rbcL, rpoC1, ycf1, and ycf2) were found to be under positive selection. This is an uncommon occurrence in other taxa where previous studies have only identified two or three positively selected genes [40, 55]. Therefore, the chloroplast genome characteristics observed in the five species studied indicate ongoing adaptive evolutionary processes within Styrax.

Firstly, the majority of these genes are directly involved in photosynthesis or closely related physiological processes. For instance, the atpB gene encodes a subunit of ATP synthase that is essential for photophosphorylation [56], while the rbcL gene encodes the large subunit of Rubisco, a key enzyme for CO2 fixation [57]. In the study of Polygonaceae, the atpB gene was identified as one of the genes undergoing positive selection [58]. These plants are widely distributed in northern temperate and tropical regions, often facing drought and high temperatures. The positive selection of atpB likely enhances ATP synthase activity and stability, enabling more efficient ATP synthesis under these stressful conditions and supporting photosynthesis [59]. Similarly, in Ardisia, which mostly grows in low-light forest understories, the rbcL gene was found to be positively selected [60]. This selection may optimize Rubisco activity and efficiency, improving photosynthesis in low-light environments.

The ccsA gene is involved in copper metabolism within chloroplasts, with copper serving as a cofactor for certain key enzymes in photosynthesis [61]. The ndhD gene is associated with the NADH dehydrogenase in chloroplasts and linked to the regulation of the photosynthetic electron transport chain [62, 63]. The protein encoded by the petA gene is an essential component of the photosynthetic electron transport chain [64, 65]. In studies of Scutellaria, the ccsA was found to be under positive selection, which may be related to the plant’s ability to adapt to environmental stresses such as drought and salinity [66]. Positive selection of this gene may enhance photosynthetic efficiency under adverse conditions. In Orchidaceae, the ndhD was found to be under positive selection in several species. This selection may optimize the stability of the photosynthetic electron transport chain, thereby improving photosynthetic efficiency under high light conditions [67]. In the genus Quercus, the petA gene was found to be under positive selection in some species. This selection may enhance the stability of the photosynthetic electron transport chain under drought conditions, thus improving photosynthetic efficiency [68].

The rpoC1 gene encodes a DNA-dependent RNA polymerase, which is a key component of chloroplast gene expression [69]. The ycf1 and ycf2 are two larger open reading frames (ORFs) in the chloroplast genome, and the proteins they encode play important roles in plant physiological processes. The ycf1 gene is essential for plant survival and is thought to be involved in the co-assembly and stability maintenance of photosynthesis complexes [70, 71], which are closely related to photosynthesis efficiency. In addition, limited research suggests that ycf2 may be involved in the transport and quality control of proteins within the chloroplast, and is crucial for cell survival [72]. Although the functions of ycf1 and ycf2 genes are not fully understood, they may play a role in certain biological processes of the chloroplast [73]. In Polygonaceae plants, the rpoC1 is under positive selection, likely enhancing chloroplast gene expression and photosynthetic efficiency in drought and high light conditions [58]. In Oenantheae, the ycf1 and ycf2 genes, crucial for plant survival and photosynthesis, show significant positive selection. ycf1 may stabilize photosynthetic complexes, and ycf2 may control protein quality in the chloroplast, aiding photosynthesis in low light and oxygen environments [74]. These genes have undergone positive selection, which may indicate that they play an important role in regulating chloroplast gene expression or responding to environmental changes.

Furthermore, these genes subject to positive selection may also be associated with the adaptation of plants to other abiotic environmental factors such as temperature, water availability, and salinity [75,76,77]. For instance, certain mutations could enhance the plant’s tolerance in drought or high-salt environments [78,79,80]. From an evolutionary standpoint, the positive selection of these genes reflects the long-term adaptation of plants to their environment. This process may involve speciation, ecological niche variations, and the generation of biodiversity [81,82,83].

Overall, the eight genes under positive selection can be categorized into three classes based on their functions. The positive selection of these genes may enhance the photosynthetic efficiency, optimize energy utilization, and improve environmental adaptability of the five rare species studied, thereby aiding the plants in better survival and reproduction in complex natural environments. Specifically, the positive selection of atpB, rbcL, and petA directly increases the efficiency of photosynthesis, enabling plants to perform photosynthesis more effectively under different light conditions. The positive selection of ccsA and ndhD optimizes the process of energy utilization, enhancing the stability and efficiency of photosynthesis. The positive selection of ycf1 and ycf2 improves the adaptability of plants under adverse conditions, strengthening their survival and reproductive capabilities. The combined action of the positive selection of these genes enables plants to better adapt and survive in complex natural environments. Through these studies, we can gain a better understanding of the molecular mechanisms of plant adaptive evolution and potentially provide new strategies for plant improvement and ecological conservation in an academic context.

Phylogenetic analysis

The results of the phylogenetic analysis indicated that the relationships among S. argentifolius, S. chrysocarpus, and S. buchananii were stable in both the CDS-based and complete chloroplast genome-based trees. However, conflicts were observed in the relationship between S. finlaysonianus and S. rhytidocarpus. Despite these differences, the overall positions of each species were generally consistent with previous research [5, 40].

The conflicting relationships between evolutionary trees constructed from CDS sequences and complete chloroplast genomes pose a complex problem, potentially arising from multiple factors. Firstly, the two phylogenetic trees constructed are both maternally inherited. However, the reasons for the conflicts in phylogeny inferred from chloroplast genomes remain unclear. A similar situation has been observed in the genus Gentiana [84], where possible causes such as heterogeneous recombination in the plastid genome and a complex history of structural evolution have been proposed [16, 85, 86]. Although no studies have detected recombination in the Styrax chloroplast genome, the possibility of plastid recombination cannot be ruled out.

Moreover, hybridization is common causes of divergent topologies in evolutionary trees built from different genomic regions [87]. Hybridization events may result in genetic recombination [88]. For instance, during the evolutionary process of Salix and Populus, there were several ancient hybridization events that led to the movement of genes between different species, causing some species’ genomes to retain genes from other species. This resulted in inconsistencies among the constructed phylogenetic trees, thereby leading to phylogenetic conflict [89]. Additionally, genetic recombination and gene loss or pseudogenes may also confound systematic signals [90]. Genetic recombination within the chloroplast genome could lead to changes in gene order, while gene loss or the emergence of pseudogenes may impact sequence-based systematic analyses [91]. Furthermore, differential rates of molecular evolution and gene selection might also contribute to divergent trees based on various genomic regions. Some genes may exhibit varying evolutionary rates and patterns due to the influence of natural selection [92].

In addition to the five mentioned species, this study observed a phenomenon of low support for certain species. Given the whole scale of this genus, it is possible that only a portion of the true current systematic evolutionary relationships has been reconstructed. We speculate that the primary reason for this issue lies in the quantity of samples used to construct phylogenetic relationships. Firstly, an increase in sample size can significantly enhance the statistical power of phylogenetic analysis. More samples yield more genetic variation information, aiding in more accurate inference of evolutionary relationships between species and reducing uncertainty in tree topology [93]. Secondly, an increased sample size helps mitigate sampling bias and provides a more comprehensive view of genetic diversity, thereby improving tree resolution and making differentiation between closely related species or populations clearer [94]. Conversely, a reduction in sample size may lead to increased uncertainty in analysis results and raise the risk of misjudging evolutionary relationships [95]. For example, Moritz emphasized the importance of sample size in defining evolutionarily significant units within conservation biology. Insufficient samples may overlook important genetic variations and evolutionary signals, thus impacting our precise understanding of biological evolutionary history [96]. Additionally, Templeton et al. suggest that a decrease in sample size may obscure genetic structure within species, affecting our comprehension of both species formation and diversity [97].

In general, the currently available genetic data is insufficient to systematically depict the phylogenetic profile of Styrax. In the context of this study, the inclusion of five rare species has supplemented some nodes and branches. While this may seem insignificant for a genus with 130 members, we believe that further research and collection will provide new insights into Styrax and even Styracaceae.

Conclusion

This study conducted sequencing and analysis of the chloroplast genomes of five rare Styrax species, revealing unique characteristics in terms of genome structure, adaptive evolution, and phylogenetic relationships. The main findings include four aspects: (1) Despite the high similarity in chloroplast genome structures among the five species, expansion and contraction of the IR region were observed, possibly reflecting dynamic genomic responses to chloroplast genome diversity within Styrax. (2) Signs of positive selection were detected in eight genes, a rarity in other lineages. These genes are directly involved in photosynthesis or related physiological processes, suggesting potential adaptation of Styrax species to diverse environmental conditions. (3) Conflict was observed among certain species in the phylogenetic tree constructed based on CDS sequences and complete chloroplast genomes, potentially attributed to factors such as gene flow, hybridization, genetic recombination, and gene loss. (4) This study underscores the importance of increasing sample sizes to enhance statistical power in phylogenetic analyses while reducing sampling bias and more comprehensively reflecting genetic diversity.

In conclusion, this study has not only advanced our understanding of the evolution of chloroplast genomes in Styrax species, but also laid a solid foundation for further research in evolutionary biology, ecology, and conservation biology. Considering the ecological and economic significance of Styrax species, the findings of this study hold important implications for the conservation and sustainable utilization of these species.

Materials and methods

Plant materials, genomic Dna isolation and genome sequencing

In this research, fresh blades of five species were collected from S. argentifolius (N 22.91, E 103.71)(Pingbian county, Yunnan province), S. buchananii (N 24.44, E 103.71)(Yijiang county, Yunnan province), S. chrysocarpus (N 23.42, E 103.71)(Malipo county, Yunnan province), S. finlaysonianus (N 21.92, E 101.25)(Mengla county, Yunnan province), and S. rhytidocarpus (N 24.82, E 112.67)(Lianzhou city, Guangdong province). Voucher specimens of five species, identified by Prof. Ming Tang, were preserved in the Herbarium of Jiangxi Agricultural University (JXAU) with the following IDs: Zrr 14, Zrr 34, Zrr 2, Zyq&Lyl 022, and Zwy 1905. Due to the ongoing construction of the website of this herbarium, the relevant information can be obtained by sending an email to the corresponding author Prof. Ming Tang or JXAU. All five species are native to China and exemplify natural distributions. The DNA from each sample was extracted following the protocol of the Plant Genomic DNA Kit (Beijing Quanshijin Biological Co., Ltd.). The concentration and purity of the DNA were evaluated using a Nanodrop 2000 instrument (Thermo Fisher Scientific, Waltham, Massachusetts, USA). The integrity of the DNA was evaluated using agarose gel electrophoresis. Following Illumina’s standard protocol, libraries were constructed from the extracted total DNA and sequenced on the Illumina NovaSeq 6000 platform (Illumina, Cambridge, MA, USA) with paired-end reads of 150 bp. All methods are exclusively conducted on Styrax plants for experimental purposes, strictly adhering to relevant institutional, national, and international guidelines and regulations.

Chloroplast genome assembly, annotation and sequence analysis

The raw reads were filtered by CLC Genomics Workbench v9 and filtered sequences were assembled using the program SPAdes v3.13.1 [98]. The scaffolds were generated by connecting the resulting contig sequences using SSPACE v2.0 [99], followed by supplementation of the scaffolds with gap using Gapfiller v1.11 [100], the specific assembly process is placed in the Supplementary Materials.

To ensure the accuracy of chloroplast genome annotation, we initially conducted a Blast comparison of the assembled sequences with the NCBI database to identify the most suitable reference genome [101]. Subsequently, CPGAVAS2 and GeSeq were employed for chloroplast genome annotation [102, 103]. The resulting annotations were manually refined and corrected using Geneious v9.0.2 (Biomatters Ltd., Auckland, New Zealand), ultimately yielding precise annotation results.

The online tool REPuter is utilized to determine the size and location of forward, reverse, palindromic, and complementary repeats in the chloroplast genome [104]. Identification of Simple sequence Repeats (SSRs) using MISA v2.1(MIcroSAtellite Identification Tool) source code, including mono-, di-, tri-, tetra-, penta-, and hexa-nucleotides, minimum number (thresholds) were 10, 6, 5, 5, 5, and 5, respectively [105]. The chloroplast genome sequences were uploaded in GenBank (Accession Number: PQ276582-PQ276586).

In order to identify the inversion and rearrangement of chloroplast genomes, a comparison was conducted on 10 Styrax species (including five in this study) using the Mauve v2.3.1 plugin Geneious [106].

Analysis of codon usage bias and selective pressures in the evolution

PhyloSuite v1.2.3 is employed to extract the full-length CDS sequence and concentration [107]. Subsequently, CodonW v1.4.2 is utilized for multiple analyses, including nucleotide compositions at the third position (A3s, U3s and G3s), GC content at third codon positions (GC3s), codon adaptation index (CAI), codon bias index (CBI), effective number of codons (ENC), and relative synonymous codon usage (RSCU).

To calculate the substitution rates of synonymous (Ks) and non-synonymous (Ka), as well as their ratios (Ka/Ks values), a total of 80 common protein coding sequences were extracted and aligned using MAFFT v7.526 [108]. The YN model, widely used in evolutionary studies, is capable of reflecting the evolutionary characteristics of sequences [109, 110]. Therefore, we utilized the YN algorithm in KaKs calculator v3.0 to compute the selection pressure and Ka/Ks values [111]. A Ka/Ks value less than 1 indicates negative selection (purification selection), while a value equal to 1 suggests neutral selection. A Ka/Ks value greater than 1 signifies positive selection (adaptive selection). It should be noted that in some cases, invalid results may occur when either Ka or Ks equals 0.

Comparative analysis

The chloroplast genome typically consists of a large single copy region (LSC), a small single copy region (SSC), and a pair of invert repeat regions (IR). While the structure of the chloroplast remains relatively stable, variations in boundary genes and the length of each region reflect interspecific divergence and evolutionary characteristics to some extent. Therefore, IRscope was utilized for analyzing the five species and their sibling species in this study [112]. Additionally, the Shuffle-LAGAN model within mVISTA was employed to uncover genome differentiation and mutation hotspots [113]. DNAsp v6.12.03 was used for calculating nucleotide polymorphisms (Pi) in CDS sequences and complete chloroplast genomes [114], the analysis employed a step size of 50 bp with a window length of 600 bp.

Phylogenetic analysis

Complete chloroplast genome samples from 32 Styrax, and 2 Sinojackia as outgroup were utilized as the database for phylogenetic analysis. The optimal model was determined using ModelFinder [115]. The complete chloroplast genome was then constructed with phylogenetic structures using the maximum likelihood method (ML) in IQ-tree v1.6.12 [116], with 1000 bootstrap replicates. Additionally, the CDS sequence using the Markov Chain Monte Carlo (MCMC) algorithm in MrBayes v3.2.7 [117], with 1,000,000 generations and sampling every 1,000 generations. The first 25% of trees from all runs were discarded as burn-in, and the remaining trees were used to create a majority-rule consensus tree through Bayesian inference (BI).

Data availability

The original contributions presented in this study are publicly available. These data can be found here: NCBI(Accession Number: PQ276582-PQ276586).

References

  1. Douglas SE. Plastid evolution: origins, diversity, trends. Curr Opin Genet Dev. 1998;8(6):655–61.

    Article  CAS  PubMed  Google Scholar 

  2. Prabhudas SK, Prayaga S, Madasamy P, Natarajan P. Shallow whole genome sequencing for the assembly of complete Chloroplast genome sequence of Arachis hypogaea L. Front Plant Sci. 2016; 7.

  3. Shinozaki K, Ohme M, Tanaka M, Wakasugi T, Hayashida N, Matsubayashi T, Zaita N, Chunwongse J, Obokata J, Yamaguchi-Shinozaki K, et al. The complete nucleotide sequence of the tobacco Chloroplast genome: its gene organization and expression. EMBO J. 1986;5(9):2043–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Sassenrath-Cole GF. Photosynthesis, A comprehensive treatise. Crop Sci. 1999;39(1):cropsci19990011183X003900010046x.

    Article  Google Scholar 

  5. Song Y, Zhao WJ, Xu J, Li MF, Zhang YJ. Chloroplast Genome Evolution and Species Identification of Styrax (Styracaceae). Biomed Res Int. 2022;2022.

  6. Alkatib S, Fleischmann TT, Scharff LB, Bock R. Evolutionary constraints on the plastid tRNA set decoding methionine and isoleucine. Nucleic Acids Res. 2012;40(14):6713–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Rogalski M, Karcher D, Bock R. Superwobbling facilitates translation with reduced tRNA sets. Nat Struct Mol Biol. 2008;15(2):192–8.

    Article  CAS  PubMed  Google Scholar 

  8. Heinke L. Chilling paternal chloroplasts. Nat Rev Mol Cell Biol. 2023;24(3):166.

    Article  CAS  PubMed  Google Scholar 

  9. Dong W, Xu C, Wen J, Zhou S. Evolutionary directions of single nucleotide substitutions and structural mutations in the Chloroplast genomes of the family Calycanthaceae. BMC Evol Biol. 2020; 20(1).

  10. Zhang J, Wang Y, Chen T, Chen Q, Wang L, Liu ZS, Wang H, Xie R, He W, Li M, et al. Evolution of Rosaceae plastomes highlights unique cerasus diversification and independent origins of fruiting Cherry. Front Plant Sci. 2021;12:736053.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Cao Z, Yang L, Xin Y, Xu W, Li Q, Zhang H, Tu Y, Song Y, Xin P. Comparative and phylogenetic analysis of complete Chloroplast genomes from seven Neocinnamomum taxa (Lauraceae). Front Plant Sci. 2023; 14.

  12. Shi W, Song W, Chen Z, Cai H, Gong Q, Liu J, Shi C, Wang S. Comparative Chloroplast genome analyses of diverse Phoebe (Lauraceae) species endemic to China provide insight into their phylogeographical origin. Peerj. 2023; 11.

  13. Dong W, Xu C, Cheng T, Lin K, Zhou S. Sequencing angiosperm plastid genomes made easy: A complete set of universal primers and a case study on the phylogeny of Saxifragales. Genome Biol Evol. 2013;5(5):989–97.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Wu ZQ, Ge S. The phylogeny of the BEP clade in grasses revisited: evidence from the whole-genome sequences of chloroplasts. Mol Phylogenet Evol. 2012;62(1):573–8.

    Article  PubMed  Google Scholar 

  15. Li HT, Yi TS, Gao LM, Ma PF, Zhang T, Yang JB, Gitzendanner MA, Fritsch PW, Cai J, Luo Y, et al. Origin of angiosperms and the puzzle of the jurassic gap. Nat Plants. 2019;5(5):461–70.

    Article  PubMed  Google Scholar 

  16. Zhang R, Wang YH, Jin JJ, Stull GW, Bruneau A, Cardoso D, De Queiroz LP, Moore MJ, Zhang SD, Chen SY, et al. Exploration of plastid phylogenomic conflict yields new insights into the deep relationships of Leguminosae. Syst Biol. 2020;69(4):613–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Corriveau JL, Coleman AW. Rapid screening method to detect potential biparental inheritance of plastid DNA and results for over 200 angiosperm species. Am J Bot. 1988;75:1443–58.

    Article  Google Scholar 

  18. Joly S, McLenachan PA, Lockhart PJ. A statistical approach for distinguishing hybridization and incomplete lineage sorting. Am Nat. 2009;174(2):E54–70.

    Article  PubMed  Google Scholar 

  19. Petit RJ, Excoffier L. Gene flow and species delimitation. Trends Ecol Evol. 2009;24(7):386–93.

    Article  PubMed  Google Scholar 

  20. Song Y, Yu W-B, Tan Y, Liu B, Yao X, Jin J, Padmanaba M, Yang J-B, Corlett RT. Evolutionary comparisons of the Chloroplast genome in Lauraceae and insights into loss events in the magnoliids. Genome Biol Evol. 2017;9(9):2354–64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Chen J, Yu R, Dai J, Liu Y, Zhou R. The loss of photosynthesis pathway and genomic locations of the lost plastid genes in a holoparasitic plant Aeginetia indica. BMC Plant Biol. 2020; 20(1).

  22. Wu Z, Liao R, Yang T, Dong X, Lan D, Qin R, Liu H. Analysis of six Chloroplast genomes provides insight into the evolution of Chrysosplenium (Saxifragaceae). BMC Genomics. 2020; 21(1).

  23. Huang S. Systematic position and geographical distribution of Styracaceae. J Trop Subtropical Bot. 1994;2(4):15–30.

    CAS  Google Scholar 

  24. Fritsch PW. Phylogeny and biogeography of the flowering plant genus Styrax (Styracaceae) based on Chloroplast DNA restriction sites and DNA sequences of the internal transcribed spacer region. Mol Phylogenet Evol. 2001;19(3):387–408.

    Article  CAS  PubMed  Google Scholar 

  25. Huang Y, Fritsch P, Shi S. A revision of the imbricate group of Styrax series Cyrta (Styracaceae) in Asia. Ann Mo Bot Gard. 2003;90:491.

    Article  Google Scholar 

  26. Xia DD, Han XY, Zhang Y, Zhang N. Chemical constituents and their biological activities from genus Styrax. Pharmaceuticals. 2023; 16(7).

  27. Wang F, Wang YB, Chen H, Chen L, Liang SW, Wang SM. Two new triterpenoids from the resin of Styrax tonkinensis. J Asian Nat Prod Res. 2015;17(8):823–7.

    Article  CAS  PubMed  Google Scholar 

  28. Tong TT, Shao LL, Peng ZH. The complete Chloroplast genome of Styrax japonicus (Styracaceae), a deciduous tree distributed in East Asia. Mitochondrial DNA Part B-Resources. 2020;5(2):1863–4.

    Article  Google Scholar 

  29. Lobdell MS, Shearer K. Genome sizes, ploidy levels, and base compositions of Styrax species and cultivars. HortScience. 2022;57(3):478–84.

    Article  CAS  Google Scholar 

  30. Tian YK, Zhang YQ, Tong LL, Xu XG, Wang YB, Jiang XY, Wang HC. The complete Chloroplast genome sequence of Styrax chinensis Hu et SY Liang (Styracaceae). Mitochondrial DNA Part B-Resources. 2020;5(3):3381–3.

    Google Scholar 

  31. Tian L, Xu XG, Tong LL, Xia CL, Cheng Y. The complete Chloroplast genome sequence of Styrax serrulatus Roxburgh (Styracaceae). Mitochondrial DNA Part B-Resources. 2021;6(11):3156–8.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Fritsch PW. Phylogeny of Styrax based on morphological characters, with implications for biogeography and infrageneric classification. Syst Bot. 1999;24(3):356–78.

    Article  Google Scholar 

  33. Fritsch PW, Cruz BC, Simison WB, Campbell AJ, Harris JK. Early phylogenetic divergence of gynodioecious species warrants the recognition of subseries in Styrax series Valvatae. Syst Bot. 2015;40(4):1081–92.

    Article  Google Scholar 

  34. Ruan YQ, Yu YL, Yu F, Deng GX, Liu YL, Wu XH, Tang M. Reinstatement of the Chinese endemic species Styrax zhejiangensis. Phytokeys 2019(133):105–13.

  35. De Bustos A, Cuadrado A, Jouve N. Sequencing of long stretches of repetitive DNA. Sci Rep. 2016;6(1):36665.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Cato SA, Richardson TE. Inter- and intraspecific polymorphism at Chloroplast SSR loci and the inheritance of plastids in Pinus radiata D. Don. Theor Appl Genet. 1996;93(4):587–92.

    Article  CAS  PubMed  Google Scholar 

  37. Götz J, Leinemann L, Gailing O, Hardtke A, Caré O. Development of a highly polymorphic Chloroplast SSR set in Abies grandis with transferability to other conifer species—A promising toolkit for gene flow investigations. Ecol Evol. 2024;14(6):e11593.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Taheri S, Lee Abdullah T, Yusop MR, Hanafi MM, Sahebi M, Azizi P, Shamshiri RR. Mining and development of novel SSR markers using next generation sequencing (NGS) data in plants. Molecules. 2018; 23(2).

  39. Taheri S, Abdullah TL, Ahmad Z, Abdullah NA. Effect of acute gamma irradiation on Curcuma alismatifolia varieties and detection of DNA polymorphism through SSR marker. Biomed Res Int. 2014;2014:631813.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Zheng HZ, Dai W, Xu MH, Lin YY, Zhu XL, Long H, Tong LL, Xu XG. Intraspecific differentiation of Styrax japonicus (Styracaceae) as revealed by comparative Chloroplast and evolutionary analyses. Genes (Basel). 2024; 15(7).

  41. Morgante M, Hanafey M, Powell W. Microsatellites are preferentially associated with nonrepetitive DNA in plant genomes. Nat Genet. 2002;30(2):194–200.

    Article  CAS  PubMed  Google Scholar 

  42. Huo N, Lazo GR, Vogel JP, You FM, Ma Y, Hayden DM, Coleman-Derr D, Hill TA, Dvorak J, Anderson OD, et al. The nuclear genome of Brachypodium distachyon: analysis of BAC end sequences. Funct Integr Genomics. 2008;8(2):135–47.

    Article  CAS  PubMed  Google Scholar 

  43. Jia X, Li H, Han Y, Wang L, Lai C, Liu X, Li P, Lei Z, Zhang Y. Genome-wide microsatellite characterization and their marker development and transferability in Broussonetia species. BMC Genomics. 2025;26(1):61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Zhang XF, Landis JB, Wang HX, Zhu ZX, Wang HF. Comparative analysis of Chloroplast genome structure and molecular dating in Myrtales. BMC Plant Biol. 2021;21(1):219.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Lynch M, Koskella B, Schaack S. Mutation pressure and the evolution of organelle genomic architecture. Science. 2006;311(5768):1727–30.

    Article  CAS  PubMed  Google Scholar 

  46. Bungard RA. Photosynthetic evolution in parasitic plants: insight from the Chloroplast genome. BioEssays. 2004;26(3):235–47.

    Article  CAS  PubMed  Google Scholar 

  47. Xiong AS, Peng RH, Zhuang J, Gao F, Zhu B, Fu XY, Xue Y, Jin XF, Tian YS, Zhao W, et al. Gene duplication, transfer, and evolution in the Chloroplast genome. Biotechnol Adv. 2009;27(4):340–7.

    Article  CAS  PubMed  Google Scholar 

  48. Zhu A, Guo W, Gupta S, Fan W, Mower JP. Evolutionary dynamics of the plastid inverted repeat: the effects of expansion, contraction, and loss on substitution rates. New Phytol. 2016;209(4):1747–56.

    Article  CAS  PubMed  Google Scholar 

  49. Guo YY, Yang JX, Bai MZ, Zhang GQ, Liu ZJ. The Chloroplast genome evolution of Venus slipper (Paphiopedilum): IR expansion, SSC contraction, and highly rearranged SSC regions. BMC Plant Biol. 2021;21(1):248.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Sun M, Zhang J, Huang T, Yang M, Ma L, Duan L. Genome structure and variation of reynoutria japonica Houtt. Chloroplast genome. Sheng Wu Gong Cheng Xue Bao. 2022;38(5):1953–64.

    CAS  PubMed  Google Scholar 

  51. Krämer C, Boehm CR, Liu J, Ting MKY, Hertle AP, Forner J, Ruf S, Schöttler MA, Zoschke R, Bock R. Removal of the large inverted repeat from the plastid genome reveals gene dosage effects and leads to increased genome copy number. Nat Plants. 2024;10(6):923–35.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Fu PC, Chen SL, Sun SS, Favre A. Strong plastid degradation is consistent within section chondrophyllae, the most speciose lineage of Gentiana. Ecol Evol. 2022;12(8):e9205.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Fu PC, Sun SS, Twyford AD, Li BB, Zhou RQ, Chen SL, Gao QB, Favre A. Lineage-specific plastid degradation in subtribe Gentianinae (Gentianaceae). Ecol Evol. 2021;11(7):3286–99.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Lin CS, Chen JJW, Chiu CC, Hsiao HCW, Yang CJ, Jin XH, Leebens-Mack J, de Pamphilis CW, Huang YT, Yang LH, et al. Concomitant loss of NDH complex-related genes within Chloroplast and nuclear genomes in some orchids. Plant J. 2017;90(5):994–1006.

    Article  CAS  PubMed  Google Scholar 

  55. Dai W, Zheng HZ, Xu MH, Zhu XL, Long H, Xu XG, Fang YM. Comparative analysis of the Chloroplast genomes of the Melliodendron (Styracaceae) species: providing insights into molecular evolution and phylogenetic relationships. Int J Mol Sci. 2025; 26(1).

  56. Neupane P, Bhuju S, Thapa N, Bhattarai HK. ATP synthase: structure, function and Inhibition. Biomol Concepts. 2019;10(1):1–10.

    Article  CAS  PubMed  Google Scholar 

  57. Tabita FR. Microbial ribulose 1,5-bisphosphate carboxylase/oxygenase: A different perspective. Photosynth Res. 1999;60(1):1–28.

    Article  CAS  Google Scholar 

  58. Feng Z, Zheng Y, Jiang Y, Pei J, Huang L. Phylogenetic relationships, selective pressure and molecular markers development of six species in subfamily Polygonoideae based on complete Chloroplast genomes. Sci Rep. 2024;14(1):9783.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Ji K, Wang Y, Sun W, Lou Q, Mei H, Shen S, Chen H. Drought-responsive mechanisms in rice genotypes with contrasting drought tolerance during reproductive stage. J Plant Physiol. 2012;169(4):336–44.

    Article  CAS  PubMed  Google Scholar 

  60. Yuan L, Ni Y, Chen H, Li J, Lu Q, Wang L, Zhang X, Yue J, Yang H, Liu C. Comparative Chloroplast genomes study of five officinal Ardisia species: unraveling interspecific diversity and evolutionary insights in Ardisia. Gene. 2024;912:148349.

    Article  CAS  PubMed  Google Scholar 

  61. Xie Z. Biosynthesis of c-type cytochromes in chloroplasts: A novel pathway. Ph.D. United States -- California: University of California, Los Angeles; 1998.

  62. Li QH, He ZH, Mi HL. The research progress of Chloroplast NAD(P)H dehydrogenase (NDH) complex. Plant Physiol J. 2013;49:401–9.

    CAS  Google Scholar 

  63. Shen L, Tang K, Wang W, Wang C, Wu H, Mao Z, An S, Chang S, Kuang T, Shen J-R, et al. Architecture of the Chloroplast PSI–NDH supercomplex in Hordeum vulgare. Nature. 2022;601(7894):649–54.

    Article  CAS  PubMed  Google Scholar 

  64. Trebst A. Dynamics in Photosystem II Structure and Function. In: Ecophysiology of Photosynthesis. Edited by Schulze E-D, Caldwell MM. Berlin, Heidelberg: Springer Berlin Heidelberg; 1995: 3–16.

  65. Loiselay C, Gumpel NJ, Girard-Bascou J, Watson AT, Purton S, Wollman FA, Choquet Y. Molecular identification and function of cis- and trans-acting determinants for PetA transcript stability in Chlamydomonas reinhardtii chloroplasts. Mol Cell Biol. 2008;28(17):5529–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Wang Y, Xu C, Guo X, Wang Y, Chen Y, Shen J, He C, Yu Y, Wang Q. Phylogenomics analysis of Scutellaria (Lamiaceae) of the world. BMC Biol. 2024;22(1):185.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Liu L, Du J, Liu Z, Zuo W, Wang Z, Li J, Zeng Y. Comparative and phylogenetic analyses of nine complete Chloroplast genomes of Orchidaceae. Sci Rep. 2023;13(1):21403.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Chen X, Li B, Zhang X. Comparison of Chloroplast genomes and phylogenetic analysis of four species in Quercus section cyclobalanopsis. Sci Rep. 2023;13(1):18731.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Yang Peng YSTW. Intron loss and molecular evolution rate of rpoC1 in ferns. Chin Bull Bot. 2020;55(3):287–98.

    Google Scholar 

  70. Dong W, Xu C, Li C, Sun J, Zuo Y, Shi S, Cheng T, Guo J, Zhou S. ycf1, the most promising plastid DNA barcode of land plants. Sci Rep. 2015;5(1):8348.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Yang XF, Wang YT, Chen ST, Li JK, Shen HT, Guo FQ. PBR1 selectively controls biogenesis of photosynthetic complexes by modulating translation of the large Chloroplast gene Ycf1 in Arabidopsis. Cell Discovery. 2016; 2.

  72. Xing J, Pan J, Yi H, Lv K, Gan Q, Wang M, Ge H, Huang X, Huang F, Wang Y, et al. The plastid-encoded protein Orf2971 is required for protein translocation and Chloroplast quality control. Plant Cell. 2022;34(9):3383–99.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Schmitz-Linneweber C, Small I. Pentatricopeptide repeat proteins: a socket set for organelle gene expression. Trends Plant Sci. 2008;13(12):663–70.

    Article  CAS  PubMed  Google Scholar 

  74. Wen J, Zhu J-W, Ma X-D, Li H-M, Wu B-C, Zhou W, Yang J-X, Song C-F. Phylogenomics and adaptive evolution of hydrophytic umbellifers (tribe oenantheae, Apioideae) revealed from Chloroplast genomes. BMC Plant Biol. 2024;24(1):1140.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Zhang TX, Chen XH, Yan W, Li MM, Huang WQ, Liu Q, Li YN, Guo CH, Shu YJ. Comparative analysis of Chloroplast Pan-Genomes and transcriptomics reveals cold adaptation in Medicago sativa. Int J Mol Sci. 2024; 25(3).

  76. Fang G, Yang S, Ruan B, Liu C, Zhang A, Jiang H, Ding S, Tian B, Zhang Y, Jahan N et al. Isolation of TSCD11 gene for early Chloroplast development under high temperature in rice. Rice. 2020; 13(1).

  77. Gao S, Gao W, Liao X, Xiong C, Yu G, Yang Q, Yang C, Ye Z. The tomato WV gene encoding a thioredoxin protein is essential for Chloroplast development at low temperature and high light intensity. BMC Plant Biol. 2019; 19.

  78. Zhuang Y, Liu Y, Li Y, Wei M, Tang Y, Li P, Liu Z, Li H, Huang W, Wang S. Salt-induced chloroplast protein (SCP) is involved in plant tolerance to salt stress in Arabidopsis. J Plant Biology. 2019;62(6):429–35.

    Article  CAS  Google Scholar 

  79. Zhuang Y, Wei M, Ling C, Liu Y, Amin AK, Li P, Li P, Hu X, Bao H, Huo H et al. EGY3 mediates chloroplastic ROS homeostasis and promotes retrograde signaling in response to salt stress in Arabidopsis. Cell Rep. 2021; 36(2).

  80. Zhang Y, Zhang A, Li X, Lu C. The role of Chloroplast gene expression in plant responses to environmental stress. Int J Mol Sci. 2020;21(17):6082.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Zhang J, Wang Y, Chen T, Chen Q, Wang L, Liu Z-s, Wang H, Xie R, He W, Li M et al. Evolution of Rosaceae plastomes highlights unique cerasus diversification and independent origins of fruiting Cherry. Front Plant Sci. 2021; 12.

  82. Jiang Q, Qiu D-P, Wang Z, Li Z-Z, Yao X-H. Research progress on local adaptation in plants. Plant Sci J. 2021;39(5):559–70.

    Google Scholar 

  83. Morrow KH. Neutral and niche theory in community ecology: a framework for comparing model realism. Biology Philos. 2024;39(1):4.

    Article  Google Scholar 

  84. Sun SS, Pan ZY, Fu Y, Wang SJ, Fu PC. Rampant intraspecific variation of plastid genomes in Gentiana section chondrophyllae. Ecol Evol. 2024;14(9):e70239.

    Article  PubMed  PubMed Central  Google Scholar 

  85. Mo ZQ, Fu CN, Zhu MS, Milne RI, Yang JB, Cai J, Qin HT, Zheng W, Hollingsworth PM, Li DZ, et al. Resolution, conflict and rate shifts: insights from a densely sampled plastome phylogeny for Rhododendron (Ericaceae). Ann Bot. 2022;130(5):687–701.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Walker JF, Walker-Hale N, Vargas OM, Larson DA, Stull GW. Characterizing gene tree conflict in plastome-inferred phylogenies. PeerJ. 2019;7:e7747.

    Article  PubMed  PubMed Central  Google Scholar 

  87. Gregory TR. CHAPTER 11 - Macroevolution and the Genome. In: The Evolution of the Genome. Edited by Gregory TR. Burlington: Academic Press; 2005: 679–729.

  88. Li X, Wei G, El-Kassaby YA, Fang Y. Hybridization and introgression in sympatric and allopatric populations of four oak species. BMC Plant Biol. 2021;21(1):266.

    Article  PubMed  PubMed Central  Google Scholar 

  89. Sanderson BJ, Gambhir D, Feng GQ, Hu N, Cronk QC, Percy DM, Freaner FM, Johnson MG, Smart LB, Keefover-Ring K, et al. Phylogenomics reveals patterns of ancient hybridization and differential diversification that contribute to phylogenetic conflict in willows, poplars, and close relatives. Syst Biol. 2023;72(6):1220–32.

    Article  PubMed  Google Scholar 

  90. Xie JB, Chen SS, Xu WJ, Zhao YY, Zhang DQ. Origination and function of plant pseudogenes. Plant Signal Behav. 2019; 14(8).

  91. Lynch M, Conery JS. The origins of genome complexity. Science. 2003;302(5649):1401–4.

    Article  CAS  PubMed  Google Scholar 

  92. Yang Z, Bielawski JP. Statistical methods for detecting molecular adaptation. Trends Ecol Evol. 2000;15(12):496–503.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Hillis DM, Bull JJ. An empirical test of bootstrapping as a method for assessing confidence in phylogenetic analysis. Syst Biol. 1993;42:182–92.

    Article  Google Scholar 

  94. Nei M, Kumar S, Nei M, Kumar S. Accuracies and statistical tests of phylogenetic trees. Molecular evolution and phylogenetics. Oxford University Press; 2000. p. 0.

  95. Felsenstein J. Confidence limits on phylogenies: an approach using the bootstrap. Evolution. 1985;39(4):783–91.

    Article  PubMed  Google Scholar 

  96. Moritz C. Defining ‘evolutionarily significant units’ for conservation. Trends Ecol Evol. 1994;9(10):373–5.

    Article  CAS  PubMed  Google Scholar 

  97. Templeton AR. Basic quantitative genetic definitions and theory. In: Popul Genet Microevolutionary Theory 2021: 295–320.

  98. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S, Prjibelski AD, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biology: J Comput Mol Cell Biology. 2012;19(5):455–77.

    Article  CAS  Google Scholar 

  99. Boetzer M, Pirovano W. SSPACE-LongRead: scaffolding bacterial draft genomes using long read sequence information. BMC Bioinformatics. 2014;15:211.

    Article  PubMed  PubMed Central  Google Scholar 

  100. Boetzer M, Pirovano W. Toward almost closed genomes with gapfiller. Genome Biol. 2012;13(6):R56.

    Article  PubMed  PubMed Central  Google Scholar 

  101. McGinnis S, Madden TL. BLAST: at the core of a powerful and diverse set of sequence analysis tools. Nucleic Acids Res. 2004; 32(Web Server issue):W20–25.

  102. Shi L, Chen H, Jiang M, Wang L, Wu X, Huang L, Liu C. CPGAVAS2, an integrated plastome sequence annotator and analyzer. Nucleic Acids Res. 2019;47(W1):W65–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Tillich M, Lehwark P, Pellizzer T, Ulbricht-Jones ES, Fischer A, Bock R, Greiner S. GeSeq - versatile and accurate annotation of organelle genomes. Nucleic Acids Res. 2017;45(W1):W6–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Kurtz S, Choudhuri JV, Ohlebusch E, Schleiermacher C, Stoye J, Giegerich R. REPuter: the manifold applications of repeat analysis on a genomic scale. Nucleic Acids Res. 2001;29(22):4633–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Beier S, Thiel T, Münch T, Scholz U, Mascher M. MISA-web: a web server for microsatellite prediction. Bioinf (Oxford England). 2017;33(16):2583–5.

    CAS  Google Scholar 

  106. Darling AC, Mau B, Blattner FR, Perna NT. Mauve: multiple alignment of conserved genomic sequence with rearrangements. Genome Res. 2004;14(7):1394–403.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Zhang D, Gao F, Jakovlić I, Zou H, Zhang J, Li WX, Wang GT. PhyloSuite: an integrated and scalable desktop platform for streamlined molecular sequence data management and evolutionary phylogenetics studies. Mol Ecol Resour. 2020;20(1):348–55.

    Article  PubMed  Google Scholar 

  108. Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013;30(4):772–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Yang Z, Nielsen R. Estimating synonymous and nonsynonymous substitution rates under realistic evolutionary models. Mol Biol Evol. 2000;17(1):32–43.

    Article  CAS  PubMed  Google Scholar 

  110. Zeng S, Zhou T, Han K, Yang Y, Zhao J, Liu ZL. The complete Chloroplast genome sequences of six Rehmannia species. Genes (Basel) 2017, 8(3).

  111. Zhang Z. KaKs_Calculator 3.0: calculating selective pressure on coding and Non-coding sequences. Genomics Proteom Bioinf. 2022;20(3):536–40.

    Article  CAS  Google Scholar 

  112. Amiryousefi A, Hyvönen J, Poczai P. IRscope: an online program to visualize the junction sites of Chloroplast genomes. Bioinf (Oxford England). 2018;34(17):3030–1.

    CAS  Google Scholar 

  113. Frazer KA, Pachter L, Poliakov A, Rubin EM, Dubchak I. VISTA: computational tools for comparative genomics. Nucleic Acids Res. 2004; 32(Web Server issue):W273–279.

  114. Rozas J, Ferrer-Mata A, Sánchez-DelBarrio JC, Guirao-Rico S, Librado P, Ramos-Onsins SE, Sánchez-Gracia A. DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol Biol Evol. 2017;34(12):3299–302.

    Article  CAS  PubMed  Google Scholar 

  115. Kalyaanamoorthy S, Minh BQ, Wong TKF, von Haeseler A, Jermiin LS. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat Methods. 2017;14(6):587–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Nguyen LT, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol. 2015;32(1):268–74.

    Article  CAS  PubMed  Google Scholar 

  117. Huelsenbeck JP, Ronquist F. MRBAYES: bayesian inference of phylogenetic trees. Bioinf (Oxford England). 2001;17(8):754–5.

    CAS  Google Scholar 

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Acknowledgements

We sincerely express our gratitude to Zhi Yang from the College of Life Sciences and Linjing Zhang from the College of Ecology and Environment in Nanjing Forestry University for their invaluable assistance and guidance in this research.

Funding

This study was financially supported by the National Natural Science Foundation of China (No. 31960043), Jiangxi Agricultural University, Jiangxi Provincial Key Laboratory of Conservation Biology (No. 2023SSY02081).

Author information

Author notes

  1. Hao-Zhi Zheng, Guo-Xing Peng and Liao-Cheng Zhao contributed equally to this work.

Authors and Affiliations

  1. Co-Innovation Center for Sustainable Forestry in Southern China, College of Life Science, Nanjing Forestry University, Nanjing, 210037, China

    Hao-Zhi Zheng, Wei Dai, Meng-Han Xu & Xiao-Gang Xu

  2. College of Forestry, Jiangxi Agricultural University, Nanchang, 330045, China

    Guo-Xing Peng & Ming Tang

  3. Laboratory of Systematic Evolution and Biogeography of Woody Plants, School of Ecology and Nature Conservation, Beijing Forestry University, Beijing, 100083, China

    Liao-Cheng Zhao

  4. Jiangxi Provincial Key Laboratory of Conservation Biology, Jiangxi Agricultural University, Nanchang, 330045, China

    Ming Tang

Authors
  1. Hao-Zhi Zheng
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  3. Liao-Cheng Zhao
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  4. Wei Dai
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Contributions

M.T. and X.G.X are the corresponding authors of this manuscript, with H.Z.Z, G.X.P, and L.C.Z making equal contributions to the work. W.D. completed the processing of the images, while M.H.X processed the data. H.Z.Z wrote the manuscript, G.X.P was responsible for experimental design, and L.C.Z. was responsible for methodology. M.T. provided funding support and supervised the entire work together with X.G.X.

Corresponding authors

Correspondence to Xiao-Gang Xu or Ming Tang.

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Zheng, HZ., Peng, GX., Zhao, LC. et al. Comparative and evolutionary analysis of chloroplast genomes from five rare Styrax species. BMC Genomics 26, 450 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12864-025-11629-3

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BMC Genomics

ISSN: 1471-2164

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