Skip to main content
Download PDF

The complete mitochondrial genome of Sinojackia microcarpa: evolutionary insights and gene transfer

BMC Genomics volume 26, Article number: 446 (2025) Cite this article

Abstract

Background

As a dicotyledonous plant within the Styracaceae family, Sinojackia microcarpa (S. microcarpa) is notable for its library-shaped fruit and sparse distribution, serving as a model system for studying the entire tree family. However, the scarcity of genomic data, particularly concerning the mitochondrial and nuclear sequences of S. microcarpa, has substantially impeded our understanding of its evolutionary traits and fundamental biological mechanisms.

Results

This study presents the first complete mitochondrial genome sequence of S. microcarpa and conducts a comparative analysis of its protein-encoding genes across eight plant species. Our analysis revealed that the mitochondrial genome of S. microcarpa spans 687,378 base pairs and contains a total of 59 genes, which include 37 protein-coding genes (PCGs), 20 transfer RNA (tRNA) genes, and 2 ribosomal RNA (rRNA) genes. Sixteen plastid-derived fragments strongly linked with mitochondrial genes, including one intact plastid-related gene (rps7), were identified. Additionally, Ka/Ks ratio analysis revealed that most mitochondrial genes are under purifying selection, with a few genes, such as nad9 and ccmB, showing signs of relaxed or adaptive evolution. An analysis of twenty-nine protein-coding genes from twenty-four plant species reveals that S. microcarpa exhibits a closer evolutionary relationship with species belonging to the genus Camellia. The findings of this study provide new genomic data that enhance our understanding of S. microcarpa, and reveal its mitochondrial genome’s evolutionary proximity to other dicotyledonous species.

Conclusions

Overall, this research enhances our understanding of the evolutionary and comparative genomics of S. microcarpa and other plants in the Styracaceae family and lays the foundation for future genetic studies and evolutionary analyses in the Styracaceae family.

Peer Review reports

Background

The mitochondrial genome is a crucial genetic material in eukaryotic cells, garnering significant attention due to its central role in energy metabolism [1,2,3]. Compared to the nuclear genome, the mitochondrial genome exhibits distinctive characteristics such as a smaller genome size, maternal inheritance, a circular structure, and a relatively rapid evolutionary rate [3,4,5]. It plays a pivotal role in cellular energy production and in regulating apoptosis, calcium ion homeostasis, and other vital cellular functions [6,7,8,9]. In recent years, with the advancement of high-throughput sequencing technologies, research on the mitochondrial genome has made significant progress in fields such as evolutionary biology, population genetics, and disease diagnosis [10,11,12]. Additionally, the diversity and structural variation of the mitochondrial genome offers new insights into understanding biological adaptive evolution [13,14,15]. Therefore, studying the mitochondrial genome sheds light on its functional mechanisms and broad implications for research on biological evolution and adaptation [16,17,18].

Sinojackia microcarpa Tao Chen & G. Y. Li, a deciduous large shrub in the Styracaceae family, belongs to the Sinojackia genus. It is a rare and endangered species endemic to Zhejiang Province, China, with known distributions in the Lin’an and Jiande areas [19]. Endangered plants typically refer to plant groups that can no longer reproduce or sustain their populations under natural conditions due to various endangering factors. The population size of these plants has decreased to a critical level, posing a risk of extinction [20]. China harbors a multitude of endemic species, among which a significant number of wild plants are threatened. It is estimated that over 4,000 species are at risk, accounting for 15–20% of the total species [21, 22]. In previous work, we assembled the chloroplast genome of S. microcarpa and identified rbcL as a suitable DNA barcode marker for analyzing the phylogenetic relationships within the Styracaceae family [23]. Additionally, the genetic diversity of S. microcarpa was analyzed using simple sequence repeat (SSR) markers [24, 25]. However, our work is still insufficient. To further study and understand Sinojackia microcarpa, we have assembled and annotated its mitochondrial genome, aiming to gain a better understanding of this species and improve the conservation of these valuable biological resources. These biological resources are valuable for scientific research and may contribute to a better understanding of biological mechanisms, with potential applications in various fields.

The formation, development, endangerment, and extinction of species encompass the entire interaction between a species and its environment, driven by both intrinsic genetic factors and external ecological conditions [26,27,28]. With advancements in research techniques and methodologies, our understanding of species formation and its underlying mechanisms has significantly deepened, surpassing that of earlier studies. Numerous plant mitochondrial genomes, including those of economically important crops such as rice (Oryza sativa), wheat (Triticum aestivum), and tobacco (Nicotiana tabacum), have been sequenced and annotated [23, 29, 30]. Mitochondrial DNA studies in plants, such as in Pinus edulis, help assess genetic diversity and population structure, providing valuable insights for developing targeted conservation strategies [31]. The study of mitochondrial genomes is crucial for understanding the evolutionary relationships, genetic diversity, and adaptive mechanisms of species. Research on the mitochondrial genome of S. microcarpa will enhance our understanding of its distinct biological mechanisms [32, 33]. No nuclear or mitochondrial genome sequences for S. microcarpa have been made available, leaving critical evolutionary traits and biological mechanisms, such as its unique fruit morphology and factors contributing to its endangered status, largely unexplored. In this study, we present the first complete mitochondrial genome of S. microcarpa, comparing its features with those of other sequenced angiosperms. Our findings provide new insights into the evolutionary characteristics of the S. microcarpa mitochondrial genome, enhancing our understanding of its biological complexity.

Results

Assembly and features of the S. microcarpa mitochondrial genome

The S. microcarpa mitochondrial genome was assembled into a single, large circular molecule, with a total length of 687,378 bp and an overall GC content of 46.24% (GenBank accession: OL693656) (Fig. 1). A total of 59 genes were identified, comprising 37 protein-coding genes (PCGs), 2 ribosomal RNA (rRNA) genes, and 20 tRNA genes, all of which were predicted and annotated using BLAST and tRNAscan-SE tools. (Table 1 and Supplemental S1). The noncoding sequence is 654,741 bp in size and accounts for 95.25% of the whole-genome sequence, which is much greater than the average noncoding sequence content (89.46%) in other angiosperms [34]. Among the 37 PCGs that are conserved among all plant mitochondrial genomes, 15 genes encode electron transport proteins and ATP synthase, including six subunits of complex I (nad3, 4, 4 l, 6, 7 and 9), one subunit of complex III (cob), three subunits of complex IV (cox1, cox2 and cox3), and five subunits of complex V (atp1, 4, 6, 8, and 9) (Supplemental Table S1). Furthermore, there were four genes for large ribosomal proteins (rpl2, 5, 11, and 16), eight genes for small ribosomal proteins (rps1, 3, 4, 7, 12, 13, 16, and 19), four genes for cytochrome c biogenesis (ccmB, ccmC, ccmFN, and ccmFC) and two genes for the maturase and transporter (matR and matB).

Fig. 1
figure 1

Circular mitochondrial genome of S. microcarpa. Genes belonging to different functional groups are color-coded. The GC content is represented on the inner circle by the dark gray plot

Full size image
Table 1 The list of genes in the mitochondrial genome of S. microcarpa
Full size table

The total length of the 37 protein-coding genes (PCGs), ranging from 225 bp (atp9) to 1,968 bp (mat-R), was 23,139 bp, representing 3.37% of the mitochondrial genome. Additionally, six intron-containing genes were identified, including nad4, nad7, cox2, rpl12, ccmFC, and rps3. Of the tRNA genes, 12 were of mitochondrial origin, while eight were derived from plastids. A total of 117 open reading frames (ORFs) larger than 50 amino acids were also detected using ORF-Finder. Most open reading frames (ORFs) contain a single gene copy ranging from 150 to 1,000 bp, with only two exceeding 1,000 bp. Despite the high number of ORFs identified, none could be assigned specific functions based on protein sequence similarity. Among the 37 core protein-coding genes, most were identical to those found in the mitochondrial genome of Stewartia sinensis, except for nad1, nad2, and nad5, which were absent in S. microcarpa.

Repeat sequences in the S. microcarpa mitochondrial genome

Repetitive sequences are widespread in the mitochondrial genomes of terrestrial plants and present substantial polymorphism. These sequences frequently involve numerous genomic rearrangements, resulting in diverse stoichiometries [29, 35]. A total of 50 pairs of large repetitive sequences ranging from 78 to 4256 bp in size were identified in the S. microcarpa mitochondrial genome (Table 2). Most of these repeats were either forward or palindromic. Of the identified repeats, three (R1–R3) exceeded 1,000 bp in length, while 32 repeats (R4–R35) ranged between 100 and 999 bp. The remaining 16 repeats (R35–R50) measured between 70 and 99 bp. Each of these large repeat sequences was present in two copies. Additionally, 27 tandem repeats longer than 10 bp were detected in the S. microcarpa mitochondrial genome. (Supplemental Table S2). The length of the repeat units in these regions varied between 11 and 48 bp, with an identity percentage ranging from 80 to 100%. In total, these tandem and scattered repeat sequences accounted for 0.2% of the S. microcarpa mitochondrial genome.

Table 2 Large repeats in the S. microcarpa mitochondrial genome
Full size table

Plastid-like sequences identified in the S. microcarpa mitochondrial genome

Sequencing analyses of the nuclear, mitochondrial, and chloroplast genomes have shown that genes can move between different genomes inside a cell [36]. There has been an upsurge in the publication and analysis of data relevant to organelle genomes due to the introduction of novel methods [23, 37]. It is believed that long-term plant evolution includes gene transfer between chloroplasts and mitochondria [38, 39]. In this study, we employed BLASTn to detect sequences within the S. microcarpa mitochondrial genome that are homologous to plastid DNA. We successfully identified 16 sequence fragments that demonstrated greater than 90% nucleotide sequence identity to the corresponding plastid sequences of S. microcarpa. The identified plastid-like sequences varied in size from 28 to 468 base pairs and collectively amounted to a total length of 1785 base pairs, representing 0.26% of the entire mitochondrial genome (Table 3). Within this array, nine genes related to tRNA and six partial protein-coding genes (PCGs) were associated primarily with photosynthesis, transcription, and translation processes. Additionally, an intact plastid-derived gene, rps7, was identified in the mitochondrial genome of S. microcarpa. Collectively, these findings substantiate the prevalence of intracellular DNA transfer from plastids to mitochondria in S. microcarpa.

Table 3 Distribution of plastid-derived sequences in the S. microcarpa mitochondrial genome
Full size table

While the intercompartmental transfer of DNA sequences from plastids to mitochondria is a widespread phenomenon across terrestrial plant species, there is considerable variation in the extent and magnitude of these transferred sequences among different taxa. In S. microcarpa, a mere 0.26% of the mitochondrial genome comprises sequences of plastid origin, a proportion markedly less than the 3–6% plastid DNA typically found within the mitochondrial genomes of other plant species [23]. The reason for this might be the relatively larger size of the S. microcarpa mitochondrial genome. Moreover, in the plastid-derived sequences, most were partial sequences that showed no functionality except for some tRNA genes, which is consistent with other land plants [40]. In S. microcarpa, an intact plastid-derived rps7 gene was identified in the mitochondrial genome, which is also frequently found in most angiosperms [23]. By studying the genomes of plant chloroplasts and mitochondria, additional insights into the evolution of phylogenetic analyses and molecular markers of these specially arranged genomes can be obtained.

Relative synonymous codon usage of the S. microcarpa mitochondrial genome

Codon usage bias is thought to result from a relative balance within the cell over a long period of evolutionary selection [41,42,43]. An RSCU value greater than 1 was considered to indicate the beneficial effect of amino acids. There were 29 codons for which the RSCU > 1 (Fig. 2). The RSCU values of the start codons AUG phenylalanine (UUC) (UUU) and tryptophan (UGG) were one. The remaining mitochondrial protein-coding genes exhibited general codon usage (Fig. 2). The stop codon showed no significant bias, with all three termination codons being approximately 1. Arginine (Arg) had the highest preference for AGA codons, with an RSCU value of 1.68 (Fig. 2). Notably, cysteine (Cys) and phenylalanine (Phe) did not have strong codon usage, with maximum RSCU values less than 1.1 (Fig. 2). The results revealed that A or T nucleotides were used more frequently at the third codon position than were C or G nucleotides. This result supports the widespread phenomenon that A/T nucleotides are used more frequently at the third codon position than C/G nucleotides. The underlying reasons for this are closely related to natural selection and mutational pressure [44,45,46].

Fig. 2
figure 2

Relative synonymous codon usage. Different proportions correspond to different RSCUs

Full size image

The Non-synonymous (Ka)/synonymous (Ks) in the S. microcarpa mitochondrial genome

The Ka/Ks ratio, which compares the rate of non-synonymous substitutions (Ka) to synonymous substitutions (Ks), serves as an indicator of selective pressures acting on protein-coding genes [47]. Based on our comparative analysis, we calculated the Ka/Ks ratios for 23 mitochondrial protein-coding genes with Stewartia sinensis to evaluate the selective pressures acting on these genes (Fig. 3, Table S3). Specifically, the majority of the analyzed genes (e.g., cob, nad7, cox3, atp8, rps7, and nad4) showed Ka/Ks ratios significantly lower than 1, indicating strong evolutionary constraints and high functional conservation. This aligns with the expectation that mitochondrial genes are typically conserved to maintain essential physiological functions. Notably, two genes—nad9 (Ka/Ks = 1.21) and ccmB (Ka/Ks = 1.36)—exhibited Ka/Ks ratios greater than 1, suggesting that these genes may be undergoing positive selection, possibly related to environmental adaptation or functional divergence. These unusual evolutionary patterns merit further investigation through functional experiments and ecological analyses, to clarify the adaptive roles of nad9 and ccmB genes in future studies.

Fig. 3
figure 3

The Non-synonymous (Ka)/synonymous (Ks) ratio values for 23 mitochondrial protein-coding genes of Sinojackia microcarpa compared with the mitochondrial genome of Stewartia sinensis Ka represents the non-synonymous substitution rate, Ks represents the synonymous substitution rate, and Ka/Ks indicates the selective pressure acting on each gene

Full size image

In conclusion, the Ka/Ks analysis reinforces the evolutionary conservation of mitochondrial functions while identifying specific genes that might be undergoing adaptive evolution. Further research could focus on understanding the biological significance of these genes and their potential role in the plant’s evolutionary adaptability.

Conserved gene clusters in the S. microcarpa mitochondrial genome

Plant mitochondrial genomes exhibit high variability in gene organization due to homologous recombination, sequence duplications, genome expansion and contraction, and foreign DNA incorporation despite a low point mutation rate [48, 49]. Recombination can disrupt gene clusters and, through multiple events, generate similar gene clusters, causing significant differences in gene order [38, 39]. In this study, we compared gene order across the mitochondrial genomes of seven angiosperm species, including four monocots and three dicots, and quantified the number of syntenic gene clusters, defined as genes maintaining their relative order. The results revealed that the rps12-nad3 gene cluster was conserved across all seven mitochondrial genomes (Fig. 4; Supplemental Table S4), indicating its high level of conservation in plant mitochondrial genomes. Additionally, the rps3-rpl16 cluster (absent in Camellia sinensis), nad1-matR (absent in S. microcarpa and Oryza minuta), and rpl5-rps14 (absent in Sorghum bicolor and Oryza minuta) were retained in most species. The nad1-rpl13 cluster (absent in S. microcarpa) and atp4-nad4L were predominantly found in Gramineae (monocots) but were either absent or lost in the three dicot species.

Fig. 4
figure 4

Analysis of conservative gene clusters between the S. microcarpa mt genome and other plant mt genomes

Full size image

The variability in gene order across the species, particularly the disruption of gene clusters due to homologous recombination, supports the hypothesis of a highly dynamic mitochondrial genome [48, 49]. The presence of different gene clusters in specific lineages, such as S. microcarpa, suggests that recombination events have shaped its mitochondrial genome, leading to the diversification of these gene arrangements. These differences reflect evolutionary pressures that vary across species and might be influenced by factors like genome size, environmental adaptation, and evolutionary history [19, 50]. The rps12-nad3 cluster’s conservation across all species studied indicates its fundamental role in mitochondrial function, likely related to the electron transport chain and energy metabolism. Other conserved clusters, such as rps3-rpl16 and nad1-matR, are essential for protein synthesis and regulation, which are critical functions in maintaining mitochondrial integrity and overall cellular function. In our study, the gene clusters in the S. microcarpa mitochondrial genome appear to be mostly consistent with those of dicot, indicating the conservation of the gene orders during the evolution of dicot species.

Distribution of S. microcarpa tRNAs compared with those of other species

A complete set of tRNAs is essential for protein translation within the plant mitochondrial genome. However, during the evolutionary process in higher plants, many tRNA genes may be lost, relocated, or inactivated [48, 49, 51]. To examine the origin and distribution of these tRNA genes, tRNAscan-SE 2.0 was employed to predict the tRNAs in the S. microcarpa mitochondrial genome. Out of the 20 tRNA genes identified, 12 were of mitochondrial origin, while eight were plastid-derived (Fig. 5) [52]. A comparative analysis involving seven other monocot and dicot species indicated that certain mitochondrial tRNAs, including trnS, trnE, trnY, trnD, and trnK, were consistently present in all species, suggesting their evolutionary conservation in plant mitochondrial genomes. Conversely, other mitochondrial tRNA genes exhibited more variable distributions. Notably, trnL was absent in all monocots and dicots except Camellia tianeensis. Among the plastid-originated tRNAs, trnM, trnH, and trnN were conserved across all examined mitochondrial genomes, highlighting their phylogenetic significance [53,54,55]. TrnL was absent in all monocotyledonary and dicotyledonary species, except for Camellia tianeensis. Among the plastid-like tRNAs, three tRNAs (trnM, trnH, and trnN) were conserved in all the analyzed mitochondrial genomes.

Fig. 5
figure 5

Distribution of transfer RNA (tRNA) genes in plant mitochondrial genomes. The white boxes indicate that the gene is absent or lost in the mitochondrial genome. Yellow and green boxes indicate mitochondrial tRNA genes and plastid-derived tRNA genes, respectively, with one copy existing in each mitochondrial genome. The numbers represent the copy numbers in the mitochondrial genome

Full size image
Fig. 6
figure 6

Phylogenetic tree based on 29 homologous protein-coding genes in the mitochondrial genomes of 24 plants via maximum likelihood (ML) analysis. The numbers below the nodes are support values with ML bootstrap values. Amborella trichopoda was designated as the outgroup. Scale bar represents nucleotide substitutions per site

Full size image

Phylogenetic analysis of S. microcarpa

The maximum likelihood phylogenetic tree, constructed using twenty-nine homologous mitochondrial protein-coding genes from twenty-four plant species, provides a framework for understanding the evolutionary relationships among these taxa. At the root of the tree, basal angiosperms such as Amborella trichopoda occupy the earliest diverging branch, establishing a foundational point that reflects the ancestral state of flowering plants.

S. microcarpa’s positioning in the tree places it among dicots, specifically within a cluster that includes Stewartia and Camellia, suggesting that S. microcarpa and these species share certain evolutionary traits, potentially related to mitochondrial genome structure or other genomic features that evolved together. The high bootstrap support values for these nodes indicate robust confidence in this grouping, implying that these species share a relatively recent common ancestor. Other genera, such as Hevea (rubber tree) and Vaccinium (blueberry), are placed further apart in the tree, indicating greater evolutionary divergence (Fig. 6).

Discussion

The assembled mitochondrial genome of S. microcarpa is an essential resource that enhances our understanding of plant mitochondrial diversity and evolutionary dynamics [49]. This genome assembly helps fill a critical gap in the phylogenetic data available for the Styracaceae family, offering new insights into how mitochondrial genomes have evolved in terms of size, gene content, and structure [32].

One of the findings from this study is the significant presence of plastid-derived sequences within the mitochondrial genome [38,39,40]. The identification of sixteen plastid-like sequences, including an intact rps7 gene, highlights the dynamic nature of gene transfer between organelles. This intercompartmental gene transfer is not only pivotal in understanding organelle evolution but also raises questions about the role these genes may play in the adaptability and function of the mitochondria in S. microcarpa. Meanwhile, given the endangered status of S. microcarpa, the genetic information derived from its mitochondrial genome is vital for conservation efforts [20]. Understanding the genomic structure can help in developing strategies to monitor genetic variation and adaptability under environmental stressors, aiding in the species’ preservation and management [56]. Further studies should focus on comparative genomic analyses between S. microcarpa and other members of the Styracaceae family to better understand the evolutionary pressures that shaped their genomes [24]. Additionally, exploring the functional significance of the plastid-derived genes found in the mitochondrial genome could provide deeper insights into their roles in cellular metabolism and stress responses. Overall, the mitochondrial genome of S. microcarpa contributes to our understanding of mitochondrial genome evolution in plants and sets a foundation for future genetic studies.

Although we successfully assembled the mitochondrial genome of S. microcarpa using high-throughput sequencing technologies, we acknowledge certain limitations in the current assembly. Despite using multiple sequencing techniques, including Illumina and PacBio, the assembly is still constrained by sequencing depth and coverage. Specifically, low coverage in certain regions may result in incomplete assembly of genome fragments, potentially affecting the integrity and accuracy of the genome. The mitochondrial genome typically contains highly repetitive sequences and gene rearrangements, which present challenges for assembly. Although we made efforts to assemble the genome, the presence of repetitive sequences may have led to incomplete or inaccurate processing of these regions. As a result, some genes or regulatory regions might be missing or incomplete. This mitochondrial assembly is primarily based on the available sequencing data, and while comparisons with genomes of other species have enhanced the reliability of the assembly, some limitations of the assembly process remain. Therefore, the current assembly may not fully represent the entire complexity of the S. microcarpa mitochondrial genome. Future research could improve these limitations by increasing sequencing depth or employing more advanced assembly methods, as well as further validating gene functions.

Materials and methods

DNA sequencing and genome assembly

Sinojackia microcarpa Tao Chen & G. Y. Li was obtained from the Campus of Zhejiang A&F University Hangzhou, Zhejiang Province (30°15′52″N, 119°43′33″E), China [57]. The voucher specimens are available at the College of Forestry and Biotechnology, Zhejiang A&F University (Accession No. BR01). Total genomic DNA was extracted via a modified cetyltrimethylammonium bromide (CTAB) method and applied to 500-bp paired-end library construction via the NEBNext Ultra DNA Library Prep Kit for Illumina sequencing [58]. Sequencing was carried out on the Illumina NovaSeq 6000 platform (BIOZERON Co., Ltd., Shanghai, China). Approximately 3.66 Gb of raw data from S. microcarpa were generated with 150 bp paired-end read lengths. For the construction and sequencing of the PacBio library, more than 5 µg of sheared and concentrated DNA was subjected to size selection by Blue Pippin (Sage Science, Beverly MA, USA). Approximately 20 kb SMRTbell libraries were prepared according to the manufacturer’s instructions (PacBio, Menlo Park, CA, USA). A total of 102.6 million reads were sequenced on the PacBio Sequel platform.

De novo assembly via NOVOPlasty referencing the mt genomes of closely related species (GenBank Acc. No. NC_016004.1, NC_016005.1 and NC_016006.1)) produced 165 scaffolds in the mt genome. BLAST searches against the mitochondrial genomes of related species, such as Cucumis sativus and NOVOPlasty, revealed that a small number of possible mitochondrial reads were isolated from the pool of Illumina data. The SPAdes-3.13.0 package was used to acquire the mitochondrial Illumina reads for the purpose of performing mt genome de novo assembly [59]. Clean PacBio long reads were aligned against the NOVOPlasty- and SPAdes-assembled scaffolds via the BWA men program [60]. The Canu v2.1.1 package was used to perform self-correction and mt genome de novo assembly on all the aligned PacBio reads. Racon v1.4.3 and Pilon v1.21 were subsequently used to rectify errors [61]. The overlap and connectivity between the sequences that PacBio had assembled were then examined.

Annotation and comparison of the mitochondrial DNA sequences

The mitochondrial genes were annotated via the online GeSeq tool, with default parameters used to predict protein-coding genes and ribosome RNA (rRNA) genes [62]. Transfer RNA (tRNA) genes were identified via tRNAScan-SE 2.0 software (http://lowelab.ucsc.edu/tRNAscan-SE/) [52]. MEGA 11 was used to analyze basic sequence information such as base composition, nucleotide sequence information sites, start codons, and stop codons and to calculate relative synonymous codon usage (RSCU). The results were visualized via the R package ggplot2 [63].

Open reading frames (ORFs) that contained > 50 amino acid residues starting with methionine were predicted and annotated via ORF-Finder (http://www.ncbi.nlm.nih.gov/gorf/gorf.html) [64]. The repeat sequences were analyzed via REPuter software (http://bibiserv.techfak.unibielefeld.de/reputer) with the following parameters: the repeat sequence was at least 50 bp in length, and the repeat identity was > 90% [65]. The circular map and syntenic gene cluster maps of the plant mitochondrial genomes were created via Chloroplot (https://irscope.shinyapps.io/chloroplot/) [66].

Phylogenetic analysis

To compare the S. microcarpa mitochondrial genome with those of other plant mitochondrial genomes, twenty-three plant species, including Camellia sinensis (NC_043914.1), Cyperus esculentus (NC_058697.1), Panax ginseng (MZ389476.1), Panax quinquefolius (NC_067574.1), Hevea spruceana (NC_084328.1), Hevea brasiliensis (AP014526.1), Hevea benthamiana (OR663908.1), Hevea pauciflora (NC_080334.1), Vaccinium oldhamii (PP812361.1), Vaccinium macrocarpon (NC_023338.1), Vaccinium bracteatum (PQ283854.1), Ilex macrocarpa (NC_082235.1), Ilex metabaptista (NC_081509.1), Camellia granthamiana (NC_086761.1), Camellia oleifera (PQ557234.1), Camellia huana (PP975887.1), Camellia tianeensis (PP727208.1), Rhododendron decorum (NC_073150.1), Rhododendron simsii (NC_053763.1), Oryza minuta (NC_029816.1), Sorghum bicolor (NC_008360.1), Amborella trichopoda (KF754799.1 ~ KF754803.1) and Stewartia sinensis (NC_081928.1). Twenty-four protein-coding genes (PCGs) (atp1,atp4,atp6,atp8,atp9,ccmB, ccmC, ccmFc, ccmFn, cob, cox3,mttB, matR, nad1,nad3,nad4,nad4,nad6,nad7,nad9,rpl10,rpl16,rpl5,rps1,rps3,rps4,rps7,rps12,rps19) from each mitochondrial genome were aligned via ClustalW and manually edited to remove gaps and missing data [67]. Phylogenetic analysis was performed via MEGA 11 software with 1,000 bootstrap replicates via the best-fit model [68]. The maximum likelihood method was used to construct the original phylogenetic trees.

Conclusions

In this study, we sequenced and annotated the complete mitochondrial genome of S. microcarpa for the first time. The genome spans 687,378 bp with a glycine–cysteine (GC) content of 46.24%. A total of 59 genes were predicted, including 37 protein-coding genes (PCGs), 2 ribosomal RNA (rRNA) genes, and 20 transfer RNA (tRNA) genes. Remarkably, the noncoding regions constituted 95.25% of the genome, which is significantly higher than in other angiosperms. Additionally, we identified 16 sequences resembling those from plastids, including a fully intact plastid-related gene, rps7. Codon usage analysis demonstrated a preference for A or T nucleotides at the third codon position over C or G nucleotides. The phylogenetic analysis of 29 protein-coding genes across 24 plant species provides valuable insights into the evolutionary relationships within the plant kingdom, particularly concerning S. microcarpa. The placement of S. microcarpa close to species from the Camellia genus suggests a relatively recent common ancestor.

Data availability

The data that support the findings of this study have been deposited in the NCBI database [GenBank accession: OL 693656] (http://www.ncbi.nlm.nih.gov/).

Abbreviations

rRNA:

Ribosomal RNA

tRNA:

Transfer RNA

PCGs:

Protein-coding genes

ORF:

Open reading frame

CTAB:

Cetyltrimethylammonium bromide

RSCU:

Relative synonymous codon usage ratios

ML:

Maximum Likelihood

References

  1. Shtolz N, Mishmar D. The mitochondrial Genome–on selective constraints and signatures at the organism, cell, and single mitochondrion levels. Front Ecol Evol 2019, 7.

  2. Kumar A, Choudhary A, Munshi A. Epigenetic reprogramming of MtDNA and its etiology in mitochondrial diseases. J Physiol Biochem 2024.

  3. Chial H, Craig J. MtDNA and mitochondrial diseases. Nat Educ. 2008;1(1):217.

    Google Scholar 

  4. Wang Y-M, Zhang C-Y, Luo S-T, Ding G-H, Qiao F. Characterization and comparison of the two mitochondrial genomes in the genus Rana. 2023;14(9):1786.

  5. Zhang L, Sun K, Csorba G, Hughes AC, Jin L, Xiao Y, Feng J. Complete mitochondrial genomes reveal robust phylogenetic signals and evidence of positive selection in horseshoe bats. BMC Ecol Evol. 2021;21(1):199.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Mammucari C, Gherardi G, Rizzuto R. Structure, activity regulation, and role of the mitochondrial calcium uniporter in health and disease. 2017, 7.

  7. Wang S-F, Tseng L-M, Lee H-C. Role of mitochondrial alterations in human cancer progression and cancer immunity. J Biomed Sci. 2023;30(1):61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Moon D-O. Calcium’s role in orchestrating Cancer apoptosis: Mitochondrial-Centric perspective. 2023;24(10):8982.

  9. Romero-Garcia S, Prado-Garcia H. Mitochondrial calcium: transport and modulation of cellular processes in homeostasis and cancer (Review). Int J Oncol. 2019;54(4):1155–67.

    CAS  PubMed  Google Scholar 

  10. Clarke AC, Prost S, Stanton J-AL, White WTJ, Kaplan ME, Matisoo-Smith EA, The Genographic C. From cheek swabs to consensus sequences: an A to Z protocol for high-throughput DNA sequencing of complete human mitochondrial genomes. BMC Genomics. 2014;15(1):68.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Sosa MX, Sivakumar IKA, Maragh S, Veeramachaneni V, Hariharan R, Parulekar M, Fredrikson KM, Harkins TT, Lin J, Feldman AB, et al. Next-Generation sequencing of human mitochondrial reference genomes uncovers high heteroplasmy frequency. PLoS Comput Biol. 2012;8(10):e1002737.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Hernández CL. Mitochondrial DNA in Human Diversity and Health: From the Golden Age to the Omics Era. 2023;14(8):1534.

  13. Chen J, Zang Y, Liang S, Xue S, Shang S, Zhu M, Wang Y, Tang X. Comparative analysis of mitochondrial genomes reveals marine adaptation in seagrasses. BMC Genomics. 2022;23(1):800.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Nosek J, Tomáška Ľ. Mitochondrial genome diversity: evolution of the molecular architecture and replication strategy. Curr Genet. 2003;44(2):73–84.

    Article  CAS  PubMed  Google Scholar 

  15. Wang X, Shang Y, Wu X, Wei Q, Zhou S, Sun G, Mei X, Dong Y, Sha W, Zhang H. Divergent evolution of mitogenomics in cetartiodactyla niche adaptation. Organisms Divers Evol. 2023;23(1):243–59.

    Article  CAS  Google Scholar 

  16. da Fonseca RR, Johnson WE, O’Brien SJ, Ramos MJ, Antunes A. The adaptive evolution of the mammalian mitochondrial genome. BMC Genomics. 2008;9(1):119.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Sunnucks P, Morales HE, Lamb AM, Pavlova A, Greening C. Integrative Approaches for Studying Mitochondrial and Nuclear Genome Co-evolution in Oxidative Phosphorylation. 2017, 8.

  18. Ladoukakis ED, Zouros E. Evolution and inheritance of animal mitochondrial DNA: rules and exceptions. J Biol Research-Thessaloniki. 2017;24(1):2.

    Article  Google Scholar 

  19. Zhang J, Ye Q, Gao P, Yao X. Genetic footprints of habitat fragmentation in the extant populations of Sinojackia (Styracaceae): implications for conservation. Bot J Linn Soc. 2012;170(2):232–42.

    Article  Google Scholar 

  20. Primack RB. Essentials of conservation biology. 6th ed. Sinauer Associates. In.; 2014.

  21. Zhang Guo,Runguo Zang. Evaluation index system of endangered degree of wild plants with minimal populations in China [J]. Forest science. 2013;49(06):10–7. In.

  22. Qing M, Gang W, Wenjie L, Seyit Y, Fachun G, Yin L. Research Advances and Perspectives of Conservation Genomics of Endangered Plants. In: Endangered Species. Edited by Mohammad Manjur S. Rijeka: IntechOpen; 2023: Ch. 4.

  23. Liao X, Zhao Y, Kong X, Khan A, Zhou B, Liu D, Kashif MH, Chen P, Wang H, Zhou R. Complete sequence of Kenaf (Hibiscus cannabinus) mitochondrial genome and comparative analysis with the mitochondrial genomes of other plants. Sci Rep. 2018;8(1):12714.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Zhong T, Zhao G, Lou Y, Lin X, Guo X. Genetic diversity analysis of Sinojackia Microcarpa, a rare tree species endemic in China, based on simple sequence repeat markers. J Forestry Res. 2019;30(3):847–54.

    Article  CAS  Google Scholar 

  25. Zhuo J, Vasupalli N, Wang Y, Zhou G, Gao H, Zheng Y, Li B, Hou D, Lin X. Molecular identification of Bambusa changningensis is the natural bamboo hybrid of B. rigida × Dendrocalamus farinosus. Front Plant Sci. 2023;14:1231940.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Genetics and Conservation of Rare Plants. Oxford University Press; 1991.

  27. Chevin LM, Lande R, Mace GM. Adaptation, plasticity, and extinction in a changing environment: towards a predictive theory. PLoS Biol. 2010;8(4):e1000357.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Hernández-Yáñez H, Kim SY, Che-Castaldo JP. Demographic and life history traits explain patterns in species vulnerability to extinction. PLoS ONE. 2022;17(2):e0263504.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Guo W, Grewe F, Fan W, Young GJ, Knoop V, Palmer JD, Mower JP. Ginkgo and Welwitschia mitogenomes reveal extreme contrasts in gymnosperm mitochondrial evolution. Mol Biol Evol. 2016;33(6):1448–60.

    Article  CAS  PubMed  Google Scholar 

  30. Asaf S, Khan AL, Khan AR, Waqas M, Kang SM, Khan MA, Shahzad R, Seo CW, Shin JH, Lee IJ. Mitochondrial genome analysis of wild rice (Oryza minuta) and its comparison with other related species. PLoS ONE. 2016;11(4):e0152937.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Wang B, Wang X-R. Mitochondrial DNA capture and divergence in Pinus provide new insights into the evolution of the genus. Mol Phylogenet Evol. 2014;80:20–30.

    Article  CAS  PubMed  Google Scholar 

  32. Fritsch PW, Morton CM, Chen T, Meldrum C. Phylogeny and Biogeography of the Styracaceae. 2001, 162(S6):S95-S116.

  33. Zhang G, Gao M, Chen Y, Wang Y, Gan T, Zhu F, Liu H. The first complete mitochondrial genome of the genus Litostrophus: insights into the rearrangement and evolution of mitochondrial genomes in Diplopoda. Genes 2024, 15(2).

  34. Zhu Q, Ge S. Phylogenetic relationships among A-genome species of the genus Oryza revealed by intron sequences of four nuclear genes. New Phytol. 2005;167(1):249–65.

    Article  CAS  PubMed  Google Scholar 

  35. Fukasawa Y, Driguez P, Bougouffa S, Carty K, Putra A, Cheung MS, Ermini L. Plasticity of repetitive sequences demonstrated by the complete mitochondrial genome of Eucalyptus camaldulensis. Front Plant Sci. 2024;15:1339594.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Nguyen VB, Linh Giang VN, Waminal NE, Park HS, Kim NH, Jang W, Lee J, Yang TJ. Comprehensive comparative analysis of Chloroplast genomes from seven Panax species and development of an authentication system based on species-unique single nucleotide polymorphism markers. J Ginseng Res. 2020;44(1):135–44.

    Article  PubMed  Google Scholar 

  37. Park S, Ruhlman TA, Sabir JS, Mutwakil MH, Baeshen MN, Sabir MJ, Baeshen NA, Jansen RK. Complete sequences of organelle genomes from the medicinal plant rhazya stricta (Apocynaceae) and contrasting patterns of mitochondrial genome evolution across Asterids. BMC Genomics. 2014;15(1):405.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Timmis JN, Ayliffe MA, Huang CY, Martin W. Endosymbiotic gene transfer: organelle genomes Forge eukaryotic chromosomes. Nat Rev Genet. 2004;5(2):123–35.

    Article  CAS  PubMed  Google Scholar 

  39. Choi K, Weng ML, Ruhlman TA, Jansen RK. Extensive variation in nucleotide substitution rate and gene/intron loss in mitochondrial genomes of Pelargonium. Mol Phylogenet Evol. 2021;155:106986.

    Article  PubMed  Google Scholar 

  40. Straub SC, Cronn RC, Edwards C, Fishbein M, Liston A. Horizontal transfer of DNA from the mitochondrial to the plastid genome and its subsequent evolution in milkweeds (apocynaceae). Genome Biol Evol. 2013;5(10):1872–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Hershberg R, Petrov DA. Selection on codon bias. Annu Rev Genet. 2008;42:287–99.

    Article  CAS  PubMed  Google Scholar 

  42. Hanson G, Coller J. Codon optimality, bias and usage in translation and mRNA decay. Nat Rev Mol Cell Biol. 2018;19(1):20–30.

    Article  CAS  PubMed  Google Scholar 

  43. LaBella AL, Opulente DA, Steenwyk JL, Hittinger CT, Rokas A. Variation and selection on codon usage bias across an entire subphylum. PLoS Genet. 2019;15(7):e1008304.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Wang L, Xing H, Yuan Y, Wang X, Saeed M, Tao J, Feng W, Zhang G, Song X, Sun X. Genome-wide analysis of codon usage bias in four sequenced cotton species. PLoS ONE. 2018;13(3):e0194372.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Zhang K, Wang Y, Zhang Y, Shan X. Codon usage characterization and phylogenetic analysis of the mitochondrial genome in Hemerocallis citrina. BMC Genomic Data. 2024;25(1):6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Hu Q, Wu J, Fan C, Luo Y, Liu J, Deng Z, Li Q. Comparative analysis of codon usage bias in the Chloroplast genomes of eighteen ampelopsideae species (Vitaceae). BMC Genomic Data. 2024;25(1):80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Shtolz N, Mishmar D. The mitochondrial Genome–on selective constraints and signatures at the organism, cell, and single mitochondrion levels. 2019, 7.

  48. Sloan DB, Alverson AJ, Štorchová H, Palmer JD, Taylor DR. Extensive loss of translational genes in the structurally dynamic mitochondrial genome of the angiosperm Silene latifolia. BMC Evol Biol. 2010;10(1):274.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Mower JP, Sloan DB, Alverson AJ. Plant Mitochondrial Genome Diversity: The Genomics Revolution. In: Plant Genome Diversity Volume 1: Plant Genomes, their Residents, and their Evolutionary Dynamics. Edited by Wendel JF, Greilhuber J, Dolezel J, Leitch IJ. Vienna: Springer Vienna; 2012: 123–144.

  50. Rogers RL, Grizzard SL, Titus-McQuillan JE, Bockrath K, Patel S, Wares JP, Garner JT, Moore CC. Gene family amplification facilitates adaptation in freshwater unionid bivalve Megalonaias nervosa. Mol Ecol. 2021;30(5):1155–73.

    Article  CAS  PubMed  Google Scholar 

  51. Zhao N, Wang Y, Hua J. The roles of mitochondrion in intergenomic gene transfer in plants: A source and a pool. Int J Mol Sci 2018, 19(2).

  52. Chan PP, Lin BY, Mak AJ, Lowe TM. tRNAscan-SE 2.0: improved detection and functional classification of transfer RNA genes. Nucleic Acids Res. 2021;49(16):9077–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Wang M, Yu W, Yang J, Hou Z, Li C, Niu Z, Zhang B, Xue Q, Liu W, Ding X. Mitochondrial genome comparison and phylogenetic analysis of Dendrobium (Orchidaceae) based on whole mitogenomes. BMC Plant Biol. 2023;23(1):586.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Burgess AL, David R, Searle IR. Conservation of tRNA and rRNA 5-methylcytosine in the Kingdom Plantae. BMC Plant Biol. 2015;15(1):199.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Christensen AC. Plant mitochondrial genome evolution can be explained by DNA repair mechanisms. Genome Biol Evol. 2013;5(6):1079–86.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Jian X, Wang Y, Li Q, Miao Y. Plastid phylogenetics, biogeography, and character evolution of the Chinese endemic genus Sinojackia Hu. 2024;16(5):305.

  57. Tao C, Gen-you L. A new species of Sinojackia Hu (Styracaceae) from Zhejiang, East China. Novon. 1997;7(4):350–2.

    Article  Google Scholar 

  58. Porebski S, Bailey LG, Baum BR. Modification of a CTAB DNA extraction protocol for plants containing high polysaccharide and polyphenol components. Plant Mol Biology Report. 1997;15(1):8–15.

    Article  CAS  Google Scholar 

  59. 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 Biol. 2012;19(5):455–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Dierckxsens N, Mardulyn P, Smits G. NOVOPlasty: de Novo assembly of organelle genomes from whole genome data. Nucleic Acids Res. 2017;45(4):e18.

    PubMed  Google Scholar 

  61. Koren S, Walenz BP, Berlin K, Miller JR, Bergman NH, Phillippy AM. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res. 2017;27(5):722–36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. 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 

  63. Ito K, Murphy D. Application of ggplot2 to pharmacometric graphics. CPT Pharmacometrics Syst Pharmacol. 2013;2(10):e79.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Rombel IT, Sykes KF, Rayner S, Johnston SA. ORF-FINDER: a vector for high-throughput gene identification. Gene. 2002;282(1–2):33–41.

    Article  CAS  PubMed  Google Scholar 

  65. Kurtz S, Schleiermacher C. REPuter: fast computation of maximal repeats in complete genomes. Bioinformatics. 1999;15(5):426–7.

    Article  CAS  PubMed  Google Scholar 

  66. Zheng S, Poczai P, Hyvonen J, Tang J, Amiryousefi A. Chloroplot: an online program for the versatile plotting of organelle genomes. Front Genet. 2020;11:576124.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Li KB. ClustalW-MPI: ClustalW analysis using distributed and parallel computing. Bioinformatics. 2003;19(12):1585–6.

    Article  PubMed  Google Scholar 

  68. Tamura K, Stecher G, Kumar S. MEGA11: molecular evolutionary genetics analysis version 11. Mol Biol Evol. 2021;38(7):3022–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank Dr. Qinhui Han of Zhejiang Agriculture & Forestry University and Dr. Xujiang He of Jiangxi Agriculture University for their assistance in our research.

Funding

This work was supported by the Zhejiang Shuren University Basic Scientific Research Special Funds [2025XZ034] and the Basic Public Welfare Research Projects of Zhejiang province, China [LGN21C160015].

Author information

Author notes

  1. Tailin Zhong and Shijie Huang contributed equally to this work.

Authors and Affiliations

  1. College of Urban Construction of Zhejiang Shuren University, Key Laboratory of Pollution Exposure and Health Intervention of Zhejiang Province, Zhejiang Shuren University, Shaoxing, Zhejiang, People’s Republic of China

    Tailin Zhong & Haifei Lu

  2. National Key Laboratory for Development and Utilization of Forest Food Resources, Zhejiang A&F University, Hangzhou, 311300, China

    Shijie Huang, Rongxiu Liu & Juan Zhuo

  3. Key Laboratory of Bamboo Science and Technology of Ministry of Education, Bamboo Industry Institute, Zhejiang A&F University, Hangzhou, 311300, China

    Shijie Huang, Rongxiu Liu & Juan Zhuo

  4. Lishan Forest Farm, Xin’gan County, Xin’gan, Jiangxi, People’s Republic of China

    Chunlin Gan

  5. State-owned Paiyangshan Forest Farm in Guangxi Zhuang Autonomous Region, Ningming, Guangxi, People’s Republic of China

    Jun Fu

  6. College of Landscape Architecture, Zheiiang A&F University, Hangzhou, 311300, China

    Qixia Qian

Authors
  1. Tailin Zhong
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Shijie Huang
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Rongxiu Liu
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Juan Zhuo
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Haifei Lu
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Chunlin Gan
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Jun Fu
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Qixia Qian
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

Conceptualization, QXQ.; methodology, TLZ.; software, TLZ. and SJH; validation, TLZ, RXL. and JZ.; formal analysis, TLZ and SJH.; investigation, CLG.; resources, HFL. and RXL; data curation, JZ; writing—original draft preparation, TLZ.; writing—review and editing. HFL, CLG, JF. and QXQ.; visualization, SJH; supervision, QXQ.; project administration, QXQ.; funding acquisition, QXQ. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Qixia Qian.

Ethics declarations

Ethics approval and consent to participate

We collected fresh leaf materials of Sinojackia microcarpa for this study. The plant samples and experimental research comply with relevant institutional, national, and international guidelines and legislation. No specific permissions or licenses were required.

Consent for publication

All co-authors have approved this study, and we affirm that the manuscript has not been published in any journal.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

: Additional files: Table S1. Summary of Sinojackia microcarpa mitochondrial genome features. Table S2. Distribution of tandem repeats in the Sinojackia microcarpa mitochondrial genome. Table S3. Pairwise nonsynonymous (dN)/synonymous (dS) substitution rates among mitochondrial genes of Sinojackia microcarpa and Stewartia sinensis. Table S4. Distribution of gene clusters in the mitochondrial genomes of land plants.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhong, T., Huang, S., Liu, R. et al. The complete mitochondrial genome of Sinojackia microcarpa: evolutionary insights and gene transfer. BMC Genomics 26, 446 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12864-025-11633-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12864-025-11633-7

Keywords

BMC Genomics

ISSN: 1471-2164

Contact us