Organellar Genome Analysis of Stephania epigaea: A Medicinal Plant Endemic to Southwest China

Organellar Genome Analysis of Stephania epigaea: A Medicinal Plant Endemic to Southwest China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Organellar Genome Analysis of Stephania epigaea: A Medicinal Plant Endemic to Southwest China Jian Chen, Congwei Yang, Yingmin Zhang, Qianwen Ma, Lixin Wu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8707172/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Mitochondria and chloroplast are central organelles in plant metabolism, playing crucial roles at various developmental stages. Stephania epigaea is a traditional medicinal plant utilized by minority ethnic groups, widely employed for treating malaria and stomach pain. Understanding the organelle genomes of S. epigaea —specifically its mitochondrial and chloroplast genomes—is essential for elucidating the molecular strategies underlying this species' evolutionary adaptation. The complete mitochondrial genome of this species is 476,231 bp in length and comprises three discrete circular chromosomes together with one additional complex structure. In contrast, the chloroplast genome is 158,139 bp and exhibits the canonical circular quadripartite architecture. A homologous segment of 9,558 bp was found to be shared with the chloroplast, involving the migration 24 homologous sequences. Relative Synonymous Codon Usage (RSCU) analysis indicates that the codon preference in the chloroplast genome of S. epigaea is generally higher than that in the mitochondria. Phylogenetic analysis indicates that S. epigaea shares a close genetic relationship with the congeneric plant S. japonica , and a substantial number of homologous blocks have been identified in the synteny analysis. Selection pressure analysis shows that the most of protein-coding genes (PCGs) exhibit a Ka/Ks ratio of less than 1, suggesting that these genes tend to maintain their original functions and avoid deleterious mutations. This study has significant implications for understanding the evolutionary relationships within the genus Stephania , laying a foundation for genetic research on the traditional medicine S. epigaea . Stephania epigaea mitogenome chloroplast repeat sequence RNA-editing site phylogenetic relationships Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Stephania epigaea H. S. Lo is a deciduous, herbaceous vine belonging to the family Menispermaceae. This species is endemic to China, primarily distributed across the provinces of Yunnan, Guizhou, and Sichuan. The tuberous roots of this plant are utilized in traditional Dai medicine for their antipyretic, detoxifying, antimalarial, and analgesic properties. Modern research has demonstrated that the tubers of S. epigaea are rich in diverse bioactive alkaloids, including dicentrine, sinomenine, and cepharanthine [ 1 , 2 ]. Pharmacological investigations have further revealed that these alkaloids exhibit potent anti-inflammatory, analgesic, and antitumor activities [ 3 – 5 ]. Furthermore, S. epigaea possesses an elegant and unique appearance, along with considerable ornamental value, making it suitable for potting or cultivation in botanical gardens. Mitochondria are essential organelles in eukaryotic cells, playing a crucial role in energy conversion and molecular breakdown [ 6 , 7 ]. Specifically, they are responsible for oxidative phosphorylation, which is the primary pathway for ATP production in eukaryotes [ 8 ]. Additionally, they participate in the breakdown of carbohydrates, lipids, and proteins, supplying metabolic intermediates for cellular processes [ 9 ]. Compared to the mitogenomes of other eukaryotic lineages, plant mitochondrial genomes display remarkable structural plasticity, with size variability being one of their most prominent characteristics. The reported size range of plant mitogenomes is exceptionally broad, exhibiting nearly a 180-fold difference: from a relatively compact 66 kb in the parasitic plant Viscum scurruloideum to an extraordinarily large 11.7 Mb in the conifer Larix sibirica Ledeb [ 10 ]. Furthermore, plant mitochondrial genomes are characterized by another salient feature: a substantial presence of repetitive sequences, which may facilitate homologous recombination, leading to a variety of conformations, as observed in Melia azedarach [ 11 ]. Mutations and structural variations in plant mitochondrial gene sequences can significantly influence the expression of critical genes associated with crop yield, resistance, and fertility. One notable example is cytoplasmic male sterility (CMS), which arises from the interaction between mitochondrial genes and their coupled nuclear counterparts [ 12 , 13 ]. Abnormal recombination and non-homologous end-joining (NHEJ) frequently generate novel open reading frames (ORFs), which may give rise to chimeric genes containing mitochondrial sequences. These chimeric genes have the potential to encode transmembrane proteins, thereby disrupting flower or pollen development and resulting in CMS [ 14 ]. In the mitochondrial genomes of higher plants, chloroplast gene fragments are abundant and constitute a significant proportion of the genome; sequences derived from the nucleus are also present, indicating widespread communication among these genetic components [ 15 ]. The transfer of DNA sequences from mitochondria to the nuclear genome is primarily recognized as unidirectional, which facilitates the incorporation of numerous mitochondrial sequences into plant nuclear genomes [ 16 ]. However, advancements in high-throughput sequencing technologies have revealed that sequences from the mitochondrial genome can occasionally undergo horizontal transfer into the nuclear genome. This finding suggests that gene flow between the plant nuclear genome and the mitochondrial genome is bidirectional, contributing additional variation to the evolution of plant genomes and complicating their evolutionary relationships [ 17 , 18 ]. In recent decades, advancements in sequencing technology have led to a substantial increase in the number of published organelle genomes [ 19 ]. To date, the mitochondrial genome has been extensively utilized to investigate the evolutionary history and breeding processes of various plant species [ 20 ]. Previous research on the organelle genomes of S. epigaea has predominantly focused on the chloroplast genome or specific chloroplast DNA fragments [ 20 , 21 ]. In contrast, the mitochondrial genome of this species remains uncharacterized, a gap that has constrained comprehensive genetic studies and further evolutionary research on S. epigaea . In this study, we performed genome sequencing of S. epigaea and successfully assembled and annotated its mitochondrial and chloroplast genomes. We validated the potential mitochondrial structure through PCR amplification and Sanger sequencing. In addition, we conducted a comprehensive analysis of the repetitive sequences, codon usage bias, and intracellular gene transfer in mitochondria and chloroplasts. Finally, we constructed a phylogenetic tree using the shared protein-coding genes (PCGs) from the mitochondrial genomes of 21 species to infer the phylogenetic position of S. epigaea within the genus Stephania . The complete assembly of the S. epigaea mitochondrial genome offers a valuable resource for future evolutionary and functional studies. Materials and methods Plant materials, DNA extracting, and sequencing Plant material was collected from Longdong Mountain, Yongsheng, Lijiang, Yunnan, China (100°42′E, 26°37′N) and cultivated at the Pharmaceutical Garden, Yunnan University of Chinese Medicine (Fig. S1 ). The specimen was identified by Professor Li Guodong and is deposited in the herbarium of Yunnan University of Chinese Medicine(20231205001LY). High-quality genomic DNA was extracted using the CTAB method [ 22 ]. DNA purity and integrity were assessed using a NanoDrop One spectrophotometer and 0.7% agarose gel electrophoresis. High-quality DNA was used to construct SMRTbell libraries for sequencing on the Pacific Biosciences Revio platform. After quality filtering, we yielded 18.31 Gb of high-quality HiFi data. Genome assembly and annotation Organelle genomes were assembled from HiFi data using PMAT v1.5.3 [ 23 ]. with parameters "-t hifi -F 0.1 -g 760m" in autoMito mode, and GFA files were visualized using Bandage [ 24 ]. Assembly accuracy was validated by independent reassembly with HIMT v1.0.9 [ 25 ]. collinearity analysis revealed high concordance. Subsequently, Genome annotation employed PMGA [ 26 ] and GeSeq ( https://chlorobox.mpimp-golm.mpg.de/geseq ), followed by manual corrected the annotation results in Geneious Prime. Circular genome maps were generated using OGDRAW [ 27 ]. Identification of repetitive sequences We utilized the MISA-web program to identify simple sequence repeats (SSRs) ( https://webblast.ipk-gatersleben.de/misa/ ) [ 28 ], which specify that the minimum repeat numbers for di-, tri-, tetra-, penta-, and hexanucleotides are 10, 5, 4, 3, 3, and 3, respectively. Additionally, we identified dispersed repeats using the REPuter ( https://bibiserv.cebitec.uni-bielefeld.de/reputer ) [ 29 ], with a Hamming distance of 3, a maximum of 5,000 computed repeats, and a minimum repeat size of 30. We employed the Tandem Repeats Finder ( https://tandem.bu.edu/trf/trf.html ) [ 30 ] to identify tandem repeats, utilizing the default parameters. Codon usage analysis Single-copy protein-coding genes (PCGs) were extracted from organelle genomes using Phylosuite v1.2.3 [ 31 ]. Mitochondrial and chloroplast coding sequences of S. epigaea were analyzed using the CUSP program in EMBOSS ( https://www.bioinformatics.nl/emboss-explorer/ ) to calculate GC content at first (GC 1 ), second (GC 2 ), and third (GC 3 ) codon positions, as well as overall GC content (GC all ). The effective number of codons (ENC) was subsequently calculated for each gene using the CHIPS program in EMBOSS. Relative synonymous codon usage (RSCU) values for mitochondrial and chloroplast genes of S. epigaea were calculated using CodonW v1.4.2. Using the R package ggplot2, we generate a stacked bar chart of RSCU and an ENC-plot. The formula for the ENC standard curve is given by 2 + GC 3 + 29/(GC 3 ² + (1 - GC 3 )²). Intracellular gene transfer analysis To explored the potential migration between the cpDNA and mtDNA of S. epigaea , we employed BLASTN [ 32 ] with an E-value ≤1e − 10 and match rate ≥ 70% as the screening criterion. These results were analyzed visually using Circos [ 33 ]. Identification of RNA editing events Utilizing the PREPACT3 ( http://www.prepact.de/prepact-main.php ), we predicted the RNA editing sites for the previously extracted protein-coding genes (PCGs). Arabidopsis thaliana (NC001284.2) was chosen as the reference mitochondrial genome, with an E-value threshold established at 0.001. Collinearity and Ka/Ks analyses The mitochondrial genomes of S. epigaea and closely related species were compared using BLASTN (parameters: -evalue 1e-5 -outfmt 6). To ensure the accuracy, Homologous sequences ≥ 500 bp were retained as conserved collinear blocks and visualized across five species using NGenomeSyn v1.41 [ 34 ]. The non-synonymous (Ka) and synonymous (Ks) substitution rates (Ka/Ks ratios) for shared protein-coding genes among S. epigaea and four relatives were calculated using Ka/Ks Calculator v3.0 [ 35 ] and summarized in box plots generated with ggplot2. Construction of phylogenetic tree The other 20 species mtDNA sequences were downloaded from the NCBI and a common set of 20 genes ( atp6 , atp8 , ccmB , ccmC , cox1 , cox2 , cox3 , cytb , matR , nad1 , nad2 , nad3 , nad4 , nad4L , nad5 , nad6 , rpl5 , rpl10 , rpl16 and rps3 ) was extracted. The dataset comprised six Ranunculaceae, two Menispermaceae, four Lauraceae, five Magnoliaceae, and three Nymphaeaceae species, with Castanopsis carlesii and Quercus acutissima (Fagaceae) as outgroups. Shared gene sequences were aligned and concatenated using MAFFT in PhyloSuite v1.2.3, and refined with Gblocks [ 36 ]. The final alignment was analyzed in IQ-TREE v1.6.8 [ 37 ], with ModelFinder selecting GTR + I+G as the best-fit model, and a maximum likelihood phylogeny was inferred from 1,000 bootstrap replicates. The tree was visualized using iTOL v6 ( https://itol.embl.de/ ). Results Structural Features and Composition of S. epigaea Organelle Genomes We identified seven contigs associated with the mitochondrial genome of S. epigaea . These contigs have a total length of 466,726 bp and an average depth of 103.4x, resulting in four distinct conformations (chr1, chr2, chr3, chr4). Among these, chr2, chr3, and chr4 are circular, while chr1 exhibits a mixed structure comprising both circular and linear forms, with the linear contig2 connecting the circular contigs 1 and 3(Fig. 1 A). For the conformation of chr1, we hypothesize a possible connection method: by duplicating contig2 and combining it with contig1 and contig3 to form a circular structure, where the duplicated contig2 + and contig2- are reverse complementary sequences(Fig. 1 B).In accordance with this hypothesis, we developed four PCR primers at the junctions of the overlapping regions (p1, p2, p3, and p4) to validate mitochondrial structure(Table S1 ). Four clear and bright bands were obtained by PCR amplification and 1% agarose gel electrophoresis, these bands are consistent in size with the expected bands and sanger sequencing confirmed this connection(Fig. 1 C). The complete mitochondrial genome of S. epigaea is 476,231 bp with a GC content of 47.0%. We annotated a total of 64 genes, which include 41 protein-coding genes (PCGs), 20 transfer RNAs (tRNAs), and 3 ribosomal RNAs (rRNAs). The PCGs comprise five subunits of ATPase ( atp1 , atp4 , atp6 , atp8 , atp9 ), four components involved in cytochrome c biogenesis ( ccmB , ccmC , ccmFC , ccmFN ), one apocytochrome b ( cob ), three subunits of cytochrome c oxidase ( cox1 , cox2 , cox3 ), one maturase R ( matR ), one transport membrane protein ( mttB ), nine subunits of NADH dehydrogenase ( nad1 , nad2 , nad3 , nad4 , nad4L , nad5 , nad6 , nad7 , nad9 ), 11 small subunits of the ribosome ( rps1 , rps10 , rps11 , rps12 , rps13 , rps14 , rps19 , rps2 , rps3 , rps4 , rps7 ), four large subunits of the ribosome ( rpl10 , rpl16 , rpl2 , rpl5 ), and two subunits of succinate dehydrogenase( sdh3 , sdh4 ). In addition, nine intron-containing genes, namely ccmFC , cox2 , nad1 , nad2 , nad4 , nad5 , nad7 , rps10 , and rps3 , were identified in the mitochondrial genome. It is noteworthy that within the ccmFN gene, the premature appearance of a stop codon due to a base deletion has led to its annotation as a pseudogene (Fig. 2 A; Table 1 ). The complete chloroplast genome of S. epigaea is 158,139 bp with a GC content of 38.3%, exhibiting a typical quadripartite structure. The cpDNA comprises a Large Single Copy (LSC) region of 88,835 bp, a Small Single Copy (SSC) region of 19,796 bp, and two Inverted Repeats (IRs) regions of 24,754 bp each. We annotated a total of 130 genes, comprising 85 PCGs, 37 rRNA, and 8 tRNA. Among these genes, 17 are characterized by the presence of introns, with both ycf3 and clpP containing two introns each. The remaining 15 genes— trnK-UUU , rps16 , trnG-UCC , atpF , rpoC1 , trnL-UAA , trnV-UAC , petB , petD , rpl16 , rpl2 , ndhB , trnI-GAU , trnA-UGC , and ndhA each possess a single intron(Fig. 2 B; Table 2 ). Table 1 List of genes encoded by the mtDNA of S. epigaea Group of genes Name of genes Subunit of ATPase atp1 , atp4 , atp6 , atp8 , atp9(×2) , Cytochrome c biogenesis ccmB , ccmC , ccmFC* , #ccmFN Apocytochrome b cob Subunit of cytochrome c oxidase cox1 , cox2* , cox3 Maturase R matR Transport membrane protein mttB Subunit of NADH dehydrogenase nad1**** , nad2**** , nad3 , nad4*** , nad4L , nad5**** , nad6 , nad7**** , nad9 Small subunit of ribosome rps1 , rps10 , rps11 , rps12 , rps13 , rps14 , rps14(×2) , rps19 , rps2 , rps3* , rps4 , rps7 Large subunit of ribosome rpl10 , rpl16 , rpl2 , rpl5 , rpl5(×2) Subunit of succinate dehydrogenase sdh3 , sdh4 Ribosomal RNAs trnL-CAA , trnP-CGG* , trnC-GCA , trnD-GUC , trnE-UUC , trnE-UUC(×2) , trnF-GAA , trnG-GCC , trnH-GUG , trnK-UUU , trnM-CAU , trnI-CAU , trnfM-CAU , trnN-GUU , trnN-GUU(×2) , trnP-UGG , trnP-UGG(×2) , trnQ-UUG , trnS-GCU , trnS-UGA , trnT-GGU , trnW-CCA , trnY-GUA Transfer RNAs rrn18 , rrn26 , rrn5 Note: *:intron number;#Gene:Pseudo gene;Gene(×2):Number of copies of multi-copy genes Table 2 List of genes encoded by the cpDNA of S. epigaea Category of genes Group of genes Name of genes Genes for photosynthesis Subunits of ATP synthase atpA , atpB , atpE , atpF* , atpH , atpI Subunits of NADH-dehydrogenase ndhA* , ndhB (×2), ndhC , ndhD , ndhE , ndhF , ndhG , ndhH , ndhI , ndhJ , ndhK Subunits of cytochrome b/f complex petA* , petB* , petD* , petG , petL , petN Subunits of photosystem Ⅰ psaA , psaB , psaC , psaI , psaJ Subunits of photosystem Ⅱ psbA , psbB , psbC , psbD , psbE , psbF , psbH , psbI , psbJ , psbK , psbL , psbM , psbN , psbT , psbZ , ycf3** Subunit of rubisco rbcL Self-replication Large subunit of ribosome rpl14 , rpl16* , rpl2 (×2) * , rpl20 , rpl22 , rpl23 (×2), rpl32 , rpl33 , rpl36 dependent RNA polymerase rpoA , rpoB , rpoC1* , rpoC2 Small subunit of ribosome rps11 , rps12 (×2) ** , rps14 , rps15 , rps16* , rps18 , rps19 , rps2 , rps3 , rps4 , rps7 (×2), rps8 tRNA tRNA genes trnH-GUG , trnK-UUU* , trnQ-UUG , trnS-GCU , trnG-UCC* , trnR-UCU , trnC-GCA , trnD-GUC , trnY-GUA , trnE-UUC , trnT-GGU , trnS-UGA , trnG-GCC , trnfM-CAU , trnS-GGA , trnT-UGU , trnL-UAA* , trnF-GAA , trnV-UAC* , trnM-CAU , trnW-CCA , trnP-UGG , trnI-CAU , trnL-CAA , trnV-GAC , trnA-UGC* , trnR-ACG , trnN-GUU , trnL-UAG , trnN-GUU (×2), trnR-ACG (×2), trnA-UGC (×2)*, trnI-GAU (×2)*, trnV-GAC (×2), trnL-CAA (×2), trnI-CAU (×3) rRNA rRNA genes rrn16S (×2), rrn23S (×2), rrn4.5S (×2), rrn5S (×2) Other genes Subunit of Acetyl-CoA-carboxylase accD C-type cytochrom synthesis gene ccsA Envelop membrane protein cemA Protease clpP** Maturase matK Translational initiation factor infA Unkown Conserved open reading frames ycf1 , ycf2 (×2), ycf4 Note: Genes with one or two introns are indicated by one (*) or two asterisks (**). Genes with two copies are denoted by (x2). Repeat sequence analysis Simple sequence repeats (SSRs), also known as microsatellite DNA, are tandemly repeated sequences composed of 1–6 nucleotides and are widely distributed throughout eukaryotic genomes [ 38 ]. In this study, we detected 134 and 68 SSRs in mtDNA and cpDNA, respectively. The SSRs in mtDNA are primarily composed of monomeric and tetrameric repeats, accounting for 62.69% (84) of the total SSRs. In cpDNA, the SSRs are predominantly monomeric, accounting for 72.06% (49) of the total. Tandem repeats with longer repeat units, commonly referred to as satellite DNA, consist of repeated sequences that are typically longer than SSRs(Table S2 ). In the mitochondrial and chloroplast genomes of S. epigaea , 21 and 42 tandem repeat sequences were detected, respectively, along with 90 pairs and 29 pairs of dispersed repeat sequences (Table S3 ). Among these, the mitochondrial genome contains 41 forward repeats (F) and 49 palindromic repeats (P), while the chloroplast genome includes 14 forward repeats (F), 14 palindromic repeats (P), and one reverse repeat (R). Neither genome exhibited complementary repeats (C).In the mitochondrial genome, the longest forward repeat identified was 332 bp, whereas the longest palindromic repeat was 9,506 bp(Table S4). In contrast, in the chloroplast genome, the longest forward repeat identified was 39 bp, whereas the longest palindromic repeat was 24,754 bp(Fig. 3 ). Codon usage analysis among PCGs In the analysis of organelle genomes, the relative synonymous codon usage (RSCU) is frequently calculated to assess codon usage bias. In mtDNA, RSCU values range from 1.560 for GCT in alanine to 0.487 for TAC in tyrosine. Conversely, in cpDNA, RSCU values vary from 1.774 for TTA in leucine to 0.378 for CTC in leucine. Statistical analysis indicates that in the mt genome, there are 30 codons with RSCU values exceeding 1, while 32 codons have values below 1. In cpDNA, 31 codons exhibit RSCU values greater than 1, and 31 codons fall below this threshold. This suggests that the mtDNA may be subject to stronger mutational pressures, resulting in a slightly higher frequency of low-frequency codons, whereas the cpDNA experiences relatively balanced selective and mutational pressures. Notably, the RSCU values for TGG in tryptophan and ATG in methionine are both equal to 1, indicating that there is no codon usage bias for these codons (Fig. 4 A, 4 B; Table S5). ENC-plot analysis demonstrates that most genes in S. epigaea organelle genomes fall below theoretical expectations, indicating codon usage bias is shaped by natural selection rather than GC 3 content alone. Notably, in mitochondria, the atp4 , rps7 and rps4 genes deviate from the standard curve, while in chloroplasts, the rpl14 and ndhJ genes also exhibit significant deviations from the standard curve(Fig. 4 C, 4 D; Table S6). It is speculated that these genes have undergone strong selection during evolution, favoring the use of specific synonymous codons. Horizontal gene transfer of S. epigaea organelle genomes Intracellular gene transfer (IGT) is a pivotal mechanism driving eukaryotic evolution, through BLASTn analysis of the organelle genomes, we identified 24 homologous sequences, encompassing both genes and intergenic regions(Table S7 and Table S8). The lengths of these sequences range from 28 to 1,233 bp, with a cumulative length of 9,558 bp, which constitutes 6.04% of the chloroplast genome. We annotated these homologous sequences and found that four are fragments of chloroplast genes (psbD , ndhB , petL , petG ), along with nine complete tRNAs ( trnD-GUC , trnT-GGU , trnM-CAU , trnW-CCA , trnP-UGG , trnI-CAU , trnN-GUU , trnA-UGC , trnI-CAU ), and two complete rRNAs ( rrn4.5S , rrn23S ) (Fig. 5 ). These findings substantiate the occurrence of DNA transfer from chloroplasts to mitochondria in S. epigaea . RNA editing sites A total of 672 potential RNA editing sites were identified in the S. epigaea mitogenome (Fig. 6 ). All RNA editing sites predicted were C to U (T) base editing (Table S9). The gene nad 4 encodes the most RNA editing sites, with 52 RNA editing sites identified, followed by the gene ccmB with 40 RNA editing events; the gene sdh3 genes had only one potential RNA editing event. Remarkably, the atp1 genes displayed no editing sites. After RNA editing, some changes occur in the properties of the original amino acids, 48.07% of the amino acids were predicted to change from hydrophilic to hydrophobic, while 8.33% were predicted to change from hydrophobic to hydrophilic. It was also found three genes ( atp6 , atp9 and rps11 ) exhibit altered open reading frames due to RNA editing, which results in the production of a termination codon. Additionally, we find amino acids predicted to edit codons show a leucine bias after RNA editing, this is supported by the fact that 42.86% (288 sites) of the amino acids were converted to leucine (Table 3 ). Table 3 Prediction of RNA editing sites Type RNA -editing Number Percentage hydrophobic GCA (A) = > GUA (V) 2 29.76% GCG (A) = > GUG (V) 7 GCU (A) = > GUU (V) 3 GCC (A) = > GUC (V) 5 CUC (L) = > UUC (F) 14 CUU (L) = > UUU (F) 20 CCA (P) = > CUA (L) 53 CCC (P) = > CUC (L) 11 CCU (P) = > UUU (F) 6 CCC (P) = > UUC (F) 3 CCG (P) = > CUG (L) 40 CCU (P) = > CUU (L) 36 hydrophilic CGC (R) = > UGC (C) 14 13.39% CGU (R) = > UGU (C) 38 CAU (H) = > UAU (Y) 25 CAC (H) = > UAC (Y) 13 hydrophobic-hydrophilic CCA (P) = > UCA (S) 12 8.33% CCC (P) = > UCC (S) 15 CCG (P) = > UCG (S) 8 CCU (P) = > UCU (S) 21 hydrophilic-hydrophobic CGG (R) = > UGG (W) 37 48.07% UCA (S) = > UUA (L) 93 UCC (S) = > UUC (F) 51 UCG (S) = > UUG (L) 55 UCU (S) = > UUU (F) 58 ACA (U) = > AUA (I) 8 ACC (U) = > AUC (I) 5 ACU (U) = > AUU (I) 6 ACG (U) = > AUG (M) 10 hydrophilic-stop CGA (R) = > UGA (X) 1 0.45% CAA (Q) = > UAA (X) 2 Ka/Ks analyses To assess environmental stress effects on mitochondrial genome evolution, Ka/Ks ratios were calculated for 20 conserved protein-coding genes (PCGs) across S. epigaea , S. japonica , Aconitum kusnezoffii , Clematis dilatata , and Pulsatilla chinensis After calculation, the Ka/Ks values of most PCGs in the mitochondrial genome of S. epigaea are less than 1 suggests that most genes tend to maintain their original function and avoid deleterious mutations. It is noteworthy that some genes exhibit signs of positive selection (Ka/Ks > 1), including the nad2 , nad4 , and rps4 genes, suggests that the gene may be undergoing adaptive changes(Fig. 7 ; Table S10). Phylogenetic and collinearity analyses To ascertain the phylogenetic position of S. epigaea within Stephania , we constructed a maximum likelihood (ML) phylogeny based on 20 shared mitochondrial protein-coding genes (PCGs) across 21 species (Table S11). The dataset included representatives from five families (Ranunculaceae, Menispermaceae, Lauraceae, Magnoliaceae, Nymphaeaceae), with Castanopsis carlesii and Quercus acutissima (Fagaceae) as outgroups. ModelFinder identified GTR + I+G as the best-fitting model for the concatenated matrix. Notably, 88% of nodes received bootstrap support ≥ 90%, including 13 nodes with 100% support. (Fig. 8 ). The structure of the mitochondrial DNA phylogenetic tree aligns with the most recent taxonomic framework established by the Angiosperm Phylogeny Group (APG). S. epigaea clustered with species from the Menispermaceae family, forming a subclade that includes S. japonica , which is consistent with our expectations. To explore the homology of mitochondrial genomes between S. epigaea and its closely related species, we conducted pairwise comparisons of the mitochondrial genomes of S. epigaea with the congeneric species S. japonica and three species from the Ranunculaceae family using the Blastn, while excluding blocks shorter than 0.5 kb (Fig. 9 ; Table S12). The results indicated that there are numerous homologous collinearity blocks and inversion blocks between S. epigaea and its closely related species ( S. japonica ), with the maximum block length being 29,498 bp and a collinearity value of 98.36%, this indicated that the mitochondrial genomes of S. epigaea and S. japonica are relatively conserved and exhibit a close phylogenetic relationship. In contrast, the number of homologous collinear blocks between S. epigaea and Clematis dilatata is relatively low, and the lengths of these blocks are shorter, with a significant presence of unaligned sequence gaps. Compared to Ranunculaceae, this indicated that the S. epigaea mitochondrial genome has undergone extensive rearrangements, which leading to a differentiation in their phylogenetic relationships. Discussion Comparative Organelle Genomics: Structure and Features Mitochondria are essential ATP-generating organelles in most eukaryotic cells, powering cellular processes through oxidative phosphorylation and thus designated as cellular "powerhouses" [ 39 ]. Similarly, chloroplasts are analogous energy-transducing organelles in plant cells that convert solar energy into carbohydrates via photosynthesis, thereby fueling plant growth and development [ 40 ]. Studies of plant organelle genomes elucidate the evolutionary mechanisms of energy metabolism pathways and reveal the genetic basis of organelle functional divergence, providing insights into plant adaptive evolution [ 41 ]. Although plant mitochondrial genomes are typically depicted as circular molecules, their actual structures can vary, including linear conformations ( Quercus acutissima ) [ 42 ], branched conformations (A belmoschus esculentus ) [ 43 ], multicyclic structures ( Angelica dahurica ) [ 44 ], and complex structures ( Panax notoginseng ) [ 45 ]. Additionally, different mitochondrial conformations may also arise at various developmental stages of the plant ( Lactuca sativa ) [ 46 ]. In our study, the mitochondrial genome of S. epigaea exhibits a simpler architecture, characterized by three circular structures and one hybrid structure. This finding starkly contrasts with the complex multi-ring architecture observed in its congener, S. japonica [ 47 ]. Visualization and analysis using Bandage software revealed that this hybrid structure can be reassembled into a circular form through the duplication of shared sequences.; its disassembly process resembles that of the mitochondrial genome of Cyperus stoloniferus [ 48 ]. The authenticity of this structure was confirmed through PCR amplification and sequencing of the overlapping regions. In contrast to this relatively simple structure, many more complex architectures are found in the mitochondria of other species. For example, the mitochondrial genome of Panax notoginseng exhibits a more intricate structure, containing multiple repeating regions and circular forms [ 45 ]. Multi-circular phenomena are also prevalent in plant mitochondria; for instance, the mitochondrial genome of Angelica dahurica comprises 12 circular structures, while that of Punica granatum consists of 7 circular structures. These varying structures highlight the diversity and complexity of plant mitochondrial genomes.In contrast to mitochondrial genomes, chloroplast genomes typically exhibit a highly conserved structure and a relatively stable genome size. They form a quadripartite circular structure composed of a small single-copy region (SSC), a large single-copy region (LSC), and two inverted repeat regions (IRs). The chloroplast genome of S. epigaea exhibits a typical quadripartite conformation, with a size of 158,139 bp comparable to that of its closely related species, Stephania yunnanensis (NC_087726, 158,146 bp) and Stephania cephalantha (NC_067079, 158,052 bp). Overall, mitochondrial genomes exhibit greater complexity than chloroplast genomes. Codon Usage Divergence Codons serve as the bridge between nucleic acids and proteins in translating genetic information, reflecting the dynamic balance between natural selection and mutational bias [ 49 ]. RSCU analysis reveals that the chloroplast genome of S. epigaea contains a total of 30 codons with RSCU values exceeding 1, while the mitochondrial genome comprises 28 such codons. Notably, most codons end with A or U, reflecting a preference common in many plant species that is typically associated with abundant tRNA populations. Preferential use of A/U-ending codons in S. epigaea organelles enhances codon-tRNA binding efficiency, minimizes ribosomal pausing, and improves translational efficiency [ 50 ]. Additionally, a certain number of mutations may have accumulated in the organellar genomes of S. epigaea during evolution, and the A/U preference can compensate for the negative effects of these mutations by enhancing RNA editing efficiency. RNA editing often occurs in A/U-enriched regions, and the large number of A/U-ending codons in the organelles of S. epigaea can provide more editing sites. Post-transcriptional modifications can correct the coding errors caused by mutations, ensuring the accuracy of protein sequences [ 51 ]. ENC analysis indicates that the codon usage bias of the organellar genes in S. epigaea is generally weak. In our study, the chloroplast genome ENC values ranged from 38.39–56.37 (mean 48.62), whereas mitochondrial genome values exhibited a broader range (39.17–61.00, mean 52.73), with all genes showing weak codon usage bias (ENC > 35). Notably, the average ENC of the mitochondria is significantly higher than that of the chloroplasts, suggesting that its codon usage is less constrained by natural selection, which may be related to the unique regulatory mechanisms of mitochondrial gene expression. The ENC-GC 3 curve is a tool used to analyze codon usage preferences. ENC-GC 3 curve analysis reveals codon usage variation among genes, enabling inference of evolutionary relationships and selective pressures [ 52 ]. ENC-plot analysis reveals similarities in the regulatory mechanisms of codon usage preferences between the chloroplast and mitochondrial genomes of S. epigaea . Most genes are situated below the neutral curve of the ENC theory, indicating that their codon usage bias is regulated by both mutation and natural selection, with natural selection being the dominant factor. This finding aligns with the functional requirements of organelles: natural selection enhances the expression efficiency of core functional genes through the directional optimization of codon usage patterns, thereby ensuring the efficient progression of photosynthesis in chloroplasts and energy metabolism in mitochondria [ 53 ]. Notably, the ENC values of the mitochondrial genes atp4 , rps7 , and rps4 , as well as the chloroplast genes rpl14 and ndhJ , are significantly higher than the expected values according to the theoretical curve. This observation suggests that these genes may have undergone directional codon optimization [ 54 ]. Horizontal gene transfer between chloroplast and mitochondrial genomes Horizontal gene transfer (HGT) is a pivotal mechanism driving eukaryotic evolution, facilitating genetic recombination and functional integration among cells and organelles [ 55 ]. In this analysis, we identified 24 homologous fragments between the mitochondrial and chloroplast genomes of S. epigaea , ranging in size from 28 to 1,233 bp. The total length of these fragments is 9,588 bp, which constitutes 6.04% of the chloroplast genome length and 2.01% of the mitochondrial genome length. This proportion is significantly higher than that of its congener, S. japonica (0.87%) [ 47 ].The largest fragment detected measured 1,233 bp in length and included two complete PCGs ( petL and petG ) as well as two complete tRNA genes ( trnW-CCA and trnP-UGG ), In addition, partial fragments of the ndhB and psbD genes, along with seven complete tRNA genes ( trnD-GUC , trnT-GGU , trnM-CAU , trnI-CAU , trnN-GUU , trnA-UGC , and trnI-CAU ), have also been transferred. The results obtained for S. epigaea in this study align with the previously reported tRNA transfer events observed in S. japonica . The five tRNA genes ( trnM-CAU , trnN-GUU , trnI-CAU , trnD-GUC , and trnT-GGU ) identified as transferred in S. japonica are fully encompassed within the nine complete transferred tRNA genes found in S. epigaea . This set of shared transferred tRNA genes suggests that HGT of these tRNA genes is a conserved evolutionary feature within the genus Stephania . These shared transferred tRNA genes represent a conserved HGT event within Stephania , reflecting common selective pressures or shared genomic mechanisms favoring retention of plastid-derived tRNAs in mitochondrial genomes. RNA editing events in the mitochondrial genome of S. epigaea RNA editing denotes the addition, deletion, and substitution of bases at the RNA level, resulting in a nucleotide sequence that diverges from the genomic DNA sequence, so altering genetic information [ 56 ]. Analysis of RNA editing sites elucidates mitochondrial gene expression in plants. In our study, we identified 672 RNA editing sites in the S. epigaea mitochondrial genome, both of which were C to U editing.The number of RNA editing sites in the mitochondrial genome of S. epigaea is close to that of the closely related species S. Japonica (684) [ 47 ], the most editing sites were nad4 genes. However, atp1 genes were all failed to detect RNA editing sites.The editing sites of plant mitochondrial genes exhibit an evolutionary dynamic of "gain-loss". The editing site of the atp1 gene within the mitochondrial genome may lose its selective advantage due to DNA mutations, ultimately leading to its loss over evolutionary time [ 57 , 58 ]. We found that three genes ( atp 6, atp 9 and rps 11) exhibit altered open reading frames due to RNA editing, which results in the production of a termination codon. The generation of premature termination codons mediated by RNA editing is an important mechanism for regulating mitochondrial gene expression in plants. On the one hand, it may fine-tune mitochondrial function via truncated protein production [ 59 ]; on the other, it may function as a quality control mechanism that eliminates aberrant transcripts and prevents accumulation of defective full-length proteins [ 60 ].Furthermore, this phenomenon occurs simultaneously in the atp6 , atp9 , and rps11 genes, suggesting that RNA editing may exert a synergistic regulatory effect on these three genes, collectively influencing mitochondrial energy metabolism and the translation process. The Ka/Ks in the mitochondrial genome Ka/Ks is an important indicator used in molecular evolution studies to measure the selective pressure on gene or protein-coding sequences [ 61 ].The ka/ks analysis of S. epigaea and its closely related species, including S. japonica , A. kusnezoffii , C. dilatata , and P. chinensis , indicates that most of the ka/ks values are less than 1. This suggests that nonsynonymous substitutions are subject to negative selection, wherein deleterious mutations are purged, thus preserving the stability of protein function [ 62 ]. Positive selection signatures (ka/ks > 1) in nad2 , rps4 , nad4 , and atp6 suggest retention of beneficial mutations driving adaptive protein evolution. Both nad2 and nad4 are essential genes encoded by the plant mitochondrial genome, and their products serve as key subunits of respiratory chain complex I. Variations in their amino acid sequences directly influence electron transfer efficiency, proton transmembrane transport capacity, and ATP synthesis rates [ 63 ]. A Ka/Ks ratio greater than 1 suggests that these genes may have optimized the structural stability or functional efficiency of complex I, enabling S. epigaea to exhibit enhanced adaptability in energy metabolism under specific habitats, such as drought and high temperatures. This optimization ensures the proper functioning of the mitochondrial respiratory chain and the stability of cellular energy metabolism. Conclusion This study successfully sequenced and assembled the mitochondrial and chloroplast genomes of S. epigaea , and verified the mitochondrial structures through PCR amplification. The mitochondrial genome (466,726 bp) comprises three circular chromosomes and one complex structure, while the chloroplast genome (158,139 bp) exhibits a typical quadripartite circular architecture. We analyzed the repetitive sequences of mitochondrial and chloroplast genomes of S. epigaea , as well as the RSCU values, ENC-plot, and inter-organelle gene transfer. The comparative analysis of these two genomes enhances our understanding of the organelles in this species. We also conducted Ka/Ks analysis, collinearity analyses, and phylogenetic analysis of S. epigaea using mitochondrial data from closely related species. The analyses indicate that S. epigaea is most closely related to S. japonica . These results will aid in understanding the organellar genomic characteristics of the Stephania genus, providing important data resources for the evolutionary studies, species identification, and genetic diversity of the Stephania plants. Declarations Authors’ contributions J.C., L.W. and G.L. conceived and designed the research. J.C. and C.Y. performed the experiments. Y.Z. and Q.M. contributed to data analysis and visualization. J.C. wrote the original draft. L.W. and G.L. reviewed and edited the manuscript. All authors read and approved the final manuscript. Funding This study was supported by the 12th Five-year Key Construction Discipline of State Administration of Traditional Chinese Medicine "Dai Pharmacy"（2024SS24088、2024JS2407） Data availability The complete mitochondrial genome (GenBank accession: PX696013) and chloroplast genome (GenBank accession: PX712054) of Stephania epigaea are publicly available in GenBank. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Author details 1Yunnan Key Laboratory of Dai and Yi Medicines, Yunnan University of Chinese Medicine, Kunming, 650500, China. 2College of Chinese Material Medica, Yunnan University of Chinese Medicine, Kunming, 650500, China. References Lv J-J, Xu M, Wang D, Zhu H-T, Yang C-R, Wang Y-F, Li Y, Zhang Y-J: Cytotoxic Bisbenzylisoquinoline Alkaloids from Stephania epigaea . J Nat Prod 2013, 76(5):926-932. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8707172","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":612425911,"identity":"3dfd07a4-2c59-496c-aeb9-0f046ec774b5","order_by":0,"name":"Jian Chen","email":"","orcid":"","institution":"Yunnan University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Chen","suffix":""},{"id":612425912,"identity":"831f399d-d217-4556-8731-cca21abdaa97","order_by":1,"name":"Congwei Yang","email":"","orcid":"","institution":"Yunnan University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Congwei","middleName":"","lastName":"Yang","suffix":""},{"id":612425913,"identity":"62183d82-6056-4d87-bba3-f3d2c704d541","order_by":2,"name":"Yingmin Zhang","email":"","orcid":"","institution":"Yunnan University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yingmin","middleName":"","lastName":"Zhang","suffix":""},{"id":612425914,"identity":"e76e2ceb-1947-44ff-9bdd-910ca861bdd4","order_by":3,"name":"Qianwen Ma","email":"","orcid":"","institution":"Yunnan University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Qianwen","middleName":"","lastName":"Ma","suffix":""},{"id":612425915,"identity":"768ce1bd-ae7d-4291-8a17-d7a67507201b","order_by":4,"name":"Lixin Wu","email":"","orcid":"","institution":"Yunnan University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Lixin","middleName":"","lastName":"Wu","suffix":""},{"id":612425917,"identity":"cf66f036-bf62-4696-ad74-acae7ec9dbad","order_by":5,"name":"Guodong Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYBACPmYQyQbE7A0wsQT8WtjgWngOEKsFTkrAVRLSws5+TeJDmU2efOQbs8c8NdsY+NlzDBh+7sDnMJ4yyRnn0ooNb+eYG/Mcu80g2fPGgLH3DF4tadK8bYcTN87OMZPmbbjNYHAjx4CZsY0YLTPPQLTYE9bCfgysZb4ED9QWCcK2MFsC/ZK4gSetTHLOsds8EmeeFRzsxaOFn//4wxvAEEuc3354m8Sbmtty/O3JGx/8xKMFGIUGYMrgAAeYwQMiDuDTAEwoD8CUfAOUMQpGwSgYBaMAHQAAbdJJl4dEyxgAAAAASUVORK5CYII=","orcid":"","institution":"Yunnan University of Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Guodong","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2026-01-27 07:38:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8707172/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8707172/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105500909,"identity":"634e3a7f-0177-4650-8160-5755a185bcbb","added_by":"auto","created_at":"2026-03-26 17:26:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":127213,"visible":true,"origin":"","legend":"\u003cp\u003eContig assembly and structural verification of \u003cem\u003eS. epigaea \u003c/em\u003emtDNA. \u003cstrong\u003eA\u003c/strong\u003e The \u003cem\u003eS. epigaea\u003c/em\u003emtDNA consists of four circular structures, including Chr1, Chr2, Chr3 and Chr4. \u003cstrong\u003eB \u003c/strong\u003eSpeculation on the possible structure of Chr1, p1, p2, p2 and p4 indicates the connection regions. \u003cstrong\u003eC \u003c/strong\u003eAgarose gel electrophoresis of PCR amplification products of p1, p2, p3 and p4 regions.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8707172/v1/f7c0e356489a5f39692c800e.png"},{"id":105500897,"identity":"e973b255-9fb1-4c3f-9373-58b21d566356","added_by":"auto","created_at":"2026-03-26 17:26:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":205781,"visible":true,"origin":"","legend":"\u003cp\u003eStructural map of organelle genomes of \u003cem\u003eS. epigaea\u003c/em\u003e (A) the mtDNA(B) the cpDNA. Genes on the inner and outer sides of the circle are transcribed clockwise and counterclockwise, respectively; functional groups are distinguished by color.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8707172/v1/38e6f9986f2dd81bfdb3fc74.png"},{"id":105500907,"identity":"4c0bbd12-130b-4668-9305-78d007924112","added_by":"auto","created_at":"2026-03-26 17:26:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":204454,"visible":true,"origin":"","legend":"\u003cp\u003eThe distribution of repeat sequences in mitochondrial and chloroplast genomes.(A,B) show the distribution map of repeat sequences in the mtDNA and cpDNA of \u003cem\u003eS. epigaea\u003c/em\u003e, the outermost layer comprises the SSR sequence, while the middle layer consists of tandem repeat sequences. The innermost connections represent dispersed repeat sequences. Forward repeats are indicated by blue lines, whereas palindromic repeats are represented by orange lines.(C,D)show the relationship between the number of SSRs and dispersed repeats, with orange representing mtDNA and green representing cpDNA.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8707172/v1/5ea1e05904498833b0db7505.png"},{"id":105500899,"identity":"79ddd7c7-7bf4-4b4b-b86e-28bb6a2f0ba1","added_by":"auto","created_at":"2026-03-26 17:26:45","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":88515,"visible":true,"origin":"","legend":"\u003cp\u003eLandscape Analysis of Codon Usage Bias in the Organelle Genomes of \u003cem\u003eS. epigaea.\u003c/em\u003e(A, B) represent the RSCU distribution of mt and cp genomes, with the x-axis indicating different amino acids and the y-axis representing RSCU values. (C, D) illustrate the ENC-plot analysis of mt and cp genomes, where the x-axis corresponds to GC3s values and the y-axis denotes ENC values.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8707172/v1/965a4a0643eb5d0c56fe9e60.png"},{"id":105500900,"identity":"99b7b1fb-39a8-46b9-a801-e6242bca9f74","added_by":"auto","created_at":"2026-03-26 17:26:45","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":208431,"visible":true,"origin":"","legend":"\u003cp\u003eHomologous analysis between chloroplast and mitochondrion genomes. The blue arc represents mtDNA. The green arc represents cpDNA. The brown lines indicated the homologous fragment between chloroplast and mitochondrion genomes.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8707172/v1/32676f7a684d769ee69f1433.png"},{"id":105565993,"identity":"595d63a9-7074-415f-a51c-78773a7015d8","added_by":"auto","created_at":"2026-03-27 12:54:59","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":52884,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of RNA editing sites predicted by individual PCGs in mitochondria.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8707172/v1/2d99e794e2769216df96575d.png"},{"id":105500898,"identity":"0399cac1-b623-46c9-9a7f-7a331240e772","added_by":"auto","created_at":"2026-03-26 17:26:45","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":36232,"visible":true,"origin":"","legend":"\u003cp\u003eThe Ka/Ks ratios of 20 protein-coding genes in \u003cem\u003eS. epigaea\u003c/em\u003e and four closely related species.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8707172/v1/54f881791c7af1c8c85a0490.png"},{"id":105565908,"identity":"1ba79225-b3cf-452b-b4ac-53122dce070b","added_by":"auto","created_at":"2026-03-27 12:54:44","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":146246,"visible":true,"origin":"","legend":"\u003cp\u003eConstruction of the maximum likelihood tree based on the 21 species, the \u003cem\u003eQuercus acutissima\u003c/em\u003e was chosen as the outgroup. The number at each node is the bootstrap probability.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-8707172/v1/6becfbcabc5bfb78959d6a96.png"},{"id":105566610,"identity":"f0ed17bd-ede7-4cf8-90e1-5c715fa9b76b","added_by":"auto","created_at":"2026-03-27 12:56:48","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":248851,"visible":true,"origin":"","legend":"\u003cp\u003eThe collinearity analysis of the mitochondrial genomes of \u003cem\u003eS. epigaea\u003c/em\u003eand its closely related species is presented. The gray lines represent homologous regions, while the pink lines indicate inversion regions.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-8707172/v1/ee05e08a8b531b654077f021.png"},{"id":105570347,"identity":"291de8a0-636f-4465-952b-00f31d02876f","added_by":"auto","created_at":"2026-03-27 13:16:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2446352,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8707172/v1/5c529179-c980-4607-ae2b-b7a6af252e89.pdf"},{"id":105500901,"identity":"7e439a87-e800-4e1e-b1cf-e1d37df9ba0c","added_by":"auto","created_at":"2026-03-26 17:26:46","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3101481,"visible":true,"origin":"","legend":"","description":"","filename":"Fig.S1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8707172/v1/4ffc14535c01a045ffc17ec3.jpg"},{"id":105500905,"identity":"94c20d22-9f79-4686-949e-69c8a45dee67","added_by":"auto","created_at":"2026-03-26 17:26:46","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":310918,"visible":true,"origin":"","legend":"","description":"","filename":"fulluncroppedGels.docx","url":"https://assets-eu.researchsquare.com/files/rs-8707172/v1/d1e7ae37ffaf75098e63c6a8.docx"},{"id":105500904,"identity":"105e9758-d311-499a-8066-1cba39a0f40f","added_by":"auto","created_at":"2026-03-26 17:26:46","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":295166,"visible":true,"origin":"","legend":"","description":"","filename":"table.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8707172/v1/00c38f8c21615ef6462555a3.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Organellar Genome Analysis of Stephania epigaea: A Medicinal Plant Endemic to Southwest China","fulltext":[{"header":"Introduction","content":"\u003cp\u003e \u003cem\u003eStephania epigaea\u003c/em\u003e H. S. Lo is a deciduous, herbaceous vine belonging to the family Menispermaceae. This species is endemic to China, primarily distributed across the provinces of Yunnan, Guizhou, and Sichuan. The tuberous roots of this plant are utilized in traditional Dai medicine for their antipyretic, detoxifying, antimalarial, and analgesic properties. Modern research has demonstrated that the tubers of \u003cem\u003eS. epigaea\u003c/em\u003e are rich in diverse bioactive alkaloids, including dicentrine, sinomenine, and cepharanthine [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Pharmacological investigations have further revealed that these alkaloids exhibit potent anti-inflammatory, analgesic, and antitumor activities [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Furthermore, \u003cem\u003eS. epigaea\u003c/em\u003e possesses an elegant and unique appearance, along with considerable ornamental value, making it suitable for potting or cultivation in botanical gardens.\u003c/p\u003e \u003cp\u003eMitochondria are essential organelles in eukaryotic cells, playing a crucial role in energy conversion and molecular breakdown [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Specifically, they are responsible for oxidative phosphorylation, which is the primary pathway for ATP production in eukaryotes [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Additionally, they participate in the breakdown of carbohydrates, lipids, and proteins, supplying metabolic intermediates for cellular processes [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Compared to the mitogenomes of other eukaryotic lineages, plant mitochondrial genomes display remarkable structural plasticity, with size variability being one of their most prominent characteristics. The reported size range of plant mitogenomes is exceptionally broad, exhibiting nearly a 180-fold difference: from a relatively compact 66 kb in the parasitic plant \u003cem\u003eViscum scurruloideum\u003c/em\u003e to an extraordinarily large 11.7 Mb in the conifer \u003cem\u003eLarix sibirica\u003c/em\u003e Ledeb [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Furthermore, plant mitochondrial genomes are characterized by another salient feature: a substantial presence of repetitive sequences, which may facilitate homologous recombination, leading to a variety of conformations, as observed in \u003cem\u003eMelia azedarach\u003c/em\u003e [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Mutations and structural variations in plant mitochondrial gene sequences can significantly influence the expression of critical genes associated with crop yield, resistance, and fertility. One notable example is cytoplasmic male sterility (CMS), which arises from the interaction between mitochondrial genes and their coupled nuclear counterparts [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Abnormal recombination and non-homologous end-joining (NHEJ) frequently generate novel open reading frames (ORFs), which may give rise to chimeric genes containing mitochondrial sequences. These chimeric genes have the potential to encode transmembrane proteins, thereby disrupting flower or pollen development and resulting in CMS [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the mitochondrial genomes of higher plants, chloroplast gene fragments are abundant and constitute a significant proportion of the genome; sequences derived from the nucleus are also present, indicating widespread communication among these genetic components [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The transfer of DNA sequences from mitochondria to the nuclear genome is primarily recognized as unidirectional, which facilitates the incorporation of numerous mitochondrial sequences into plant nuclear genomes [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, advancements in high-throughput sequencing technologies have revealed that sequences from the mitochondrial genome can occasionally undergo horizontal transfer into the nuclear genome. This finding suggests that gene flow between the plant nuclear genome and the mitochondrial genome is bidirectional, contributing additional variation to the evolution of plant genomes and complicating their evolutionary relationships [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn recent decades, advancements in sequencing technology have led to a substantial increase in the number of published organelle genomes [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. To date, the mitochondrial genome has been extensively utilized to investigate the evolutionary history and breeding processes of various plant species [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Previous research on the organelle genomes of \u003cem\u003eS. epigaea\u003c/em\u003e has predominantly focused on the chloroplast genome or specific chloroplast DNA fragments [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In contrast, the mitochondrial genome of this species remains uncharacterized, a gap that has constrained comprehensive genetic studies and further evolutionary research on \u003cem\u003eS. epigaea\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eIn this study, we performed genome sequencing of \u003cem\u003eS. epigaea\u003c/em\u003e and successfully assembled and annotated its mitochondrial and chloroplast genomes. We validated the potential mitochondrial structure through PCR amplification and Sanger sequencing. In addition, we conducted a comprehensive analysis of the repetitive sequences, codon usage bias, and intracellular gene transfer in mitochondria and chloroplasts. Finally, we constructed a phylogenetic tree using the shared protein-coding genes (PCGs) from the mitochondrial genomes of 21 species to infer the phylogenetic position of \u003cem\u003eS. epigaea\u003c/em\u003e within the genus \u003cem\u003eStephania\u003c/em\u003e. The complete assembly of the \u003cem\u003eS. epigaea\u003c/em\u003e mitochondrial genome offers a valuable resource for future evolutionary and functional studies.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePlant materials, DNA extracting, and sequencing\u003c/h2\u003e \u003cp\u003ePlant material was collected from Longdong Mountain, Yongsheng, Lijiang, Yunnan, China (100\u0026deg;42\u0026prime;E, 26\u0026deg;37\u0026prime;N) and cultivated at the Pharmaceutical Garden, Yunnan University of Chinese Medicine (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The specimen was identified by Professor Li Guodong and is deposited in the herbarium of Yunnan University of Chinese Medicine(20231205001LY). High-quality genomic DNA was extracted using the CTAB method [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. DNA purity and integrity were assessed using a NanoDrop One spectrophotometer and 0.7% agarose gel electrophoresis. High-quality DNA was used to construct SMRTbell libraries for sequencing on the Pacific Biosciences Revio platform. After quality filtering, we yielded 18.31 Gb of high-quality HiFi data.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGenome assembly and annotation\u003c/h3\u003e\n\u003cp\u003eOrganelle genomes were assembled from HiFi data using PMAT v1.5.3 [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. with parameters \"-t hifi -F 0.1 -g 760m\" in autoMito mode, and GFA files were visualized using Bandage [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Assembly accuracy was validated by independent reassembly with HIMT v1.0.9 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. collinearity analysis revealed high concordance. Subsequently, Genome annotation employed PMGA [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] and GeSeq (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://chlorobox.mpimp-golm.mpg.de/geseq\u003c/span\u003e\u003cspan address=\"https://chlorobox.mpimp-golm.mpg.de/geseq\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), followed by manual corrected the annotation results in Geneious Prime. Circular genome maps were generated using OGDRAW [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eIdentification of repetitive sequences\u003c/h3\u003e\n\u003cp\u003eWe utilized the MISA-web program to identify simple sequence repeats (SSRs) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://webblast.ipk-gatersleben.de/misa/\u003c/span\u003e\u003cspan address=\"https://webblast.ipk-gatersleben.de/misa/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], which specify that the minimum repeat numbers for di-, tri-, tetra-, penta-, and hexanucleotides are 10, 5, 4, 3, 3, and 3, respectively. Additionally, we identified dispersed repeats using the REPuter (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bibiserv.cebitec.uni-bielefeld.de/reputer\u003c/span\u003e\u003cspan address=\"https://bibiserv.cebitec.uni-bielefeld.de/reputer\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], with a Hamming distance of 3, a maximum of 5,000 computed repeats, and a minimum repeat size of 30. We employed the Tandem Repeats Finder (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://tandem.bu.edu/trf/trf.html\u003c/span\u003e\u003cspan address=\"https://tandem.bu.edu/trf/trf.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] to identify tandem repeats, utilizing the default parameters.\u003c/p\u003e\n\u003ch3\u003eCodon usage analysis\u003c/h3\u003e\n\u003cp\u003eSingle-copy protein-coding genes (PCGs) were extracted from organelle genomes using Phylosuite v1.2.3 [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Mitochondrial and chloroplast coding sequences of \u003cem\u003eS. epigaea\u003c/em\u003e were analyzed using the CUSP program in EMBOSS (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bioinformatics.nl/emboss-explorer/\u003c/span\u003e\u003cspan address=\"https://www.bioinformatics.nl/emboss-explorer/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to calculate GC content at first (GC\u003csub\u003e1\u003c/sub\u003e), second (GC\u003csub\u003e2\u003c/sub\u003e), and third (GC\u003csub\u003e3\u003c/sub\u003e) codon positions, as well as overall GC content (GC\u003csub\u003eall\u003c/sub\u003e). The effective number of codons (ENC) was subsequently calculated for each gene using the CHIPS program in EMBOSS. Relative synonymous codon usage (RSCU) values for mitochondrial and chloroplast genes of \u003cem\u003eS. epigaea\u003c/em\u003e were calculated using CodonW v1.4.2. Using the R package ggplot2, we generate a stacked bar chart of RSCU and an ENC-plot. The formula for the ENC standard curve is given by 2\u0026thinsp;+\u0026thinsp;GC\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;29/(GC\u003csub\u003e3\u003c/sub\u003e\u0026sup2; + (1 - GC\u003csub\u003e3\u003c/sub\u003e)\u0026sup2;).\u003c/p\u003e\n\u003ch3\u003eIntracellular gene transfer analysis\u003c/h3\u003e\n\u003cp\u003eTo explored the potential migration between the cpDNA and mtDNA of \u003cem\u003eS. epigaea\u003c/em\u003e, we employed BLASTN [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] with an E-value \u0026le;1e\u0026thinsp;\u0026minus;\u0026thinsp;10 and match rate\u0026thinsp;\u0026ge;\u0026thinsp;70% as the screening criterion. These results were analyzed visually using Circos [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eIdentification of RNA editing events\u003c/h2\u003e \u003cp\u003eUtilizing the PREPACT3 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.prepact.de/prepact-main.php\u003c/span\u003e\u003cspan address=\"http://www.prepact.de/prepact-main.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), we predicted the RNA editing sites for the previously extracted protein-coding genes (PCGs). \u003cem\u003eArabidopsis thaliana\u003c/em\u003e (NC001284.2) was chosen as the reference mitochondrial genome, with an E-value threshold established at 0.001.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCollinearity and Ka/Ks analyses\u003c/h3\u003e\n\u003cp\u003eThe mitochondrial genomes of \u003cem\u003eS. epigaea\u003c/em\u003e and closely related species were compared using BLASTN (parameters: -evalue 1e-5 -outfmt 6). To ensure the accuracy, Homologous sequences\u0026thinsp;\u0026ge;\u0026thinsp;500 bp were retained as conserved collinear blocks and visualized across five species using NGenomeSyn v1.41 [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The non-synonymous (Ka) and synonymous (Ks) substitution rates (Ka/Ks ratios) for shared protein-coding genes among \u003cem\u003eS. epigaea\u003c/em\u003e and four relatives were calculated using Ka/Ks Calculator v3.0 [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] and summarized in box plots generated with ggplot2.\u003c/p\u003e\n\u003ch3\u003eConstruction of phylogenetic tree\u003c/h3\u003e\n\u003cp\u003eThe other 20 species mtDNA sequences were downloaded from the NCBI and a common set of 20 genes (\u003cem\u003eatp6\u003c/em\u003e, \u003cem\u003eatp8\u003c/em\u003e, \u003cem\u003eccmB\u003c/em\u003e, \u003cem\u003eccmC\u003c/em\u003e, \u003cem\u003ecox1\u003c/em\u003e, \u003cem\u003ecox2\u003c/em\u003e, \u003cem\u003ecox3\u003c/em\u003e, \u003cem\u003ecytb\u003c/em\u003e, \u003cem\u003ematR\u003c/em\u003e, \u003cem\u003enad1\u003c/em\u003e, \u003cem\u003enad2\u003c/em\u003e, \u003cem\u003enad3\u003c/em\u003e, \u003cem\u003enad4\u003c/em\u003e, \u003cem\u003enad4L\u003c/em\u003e, \u003cem\u003enad5\u003c/em\u003e, \u003cem\u003enad6\u003c/em\u003e, \u003cem\u003erpl5\u003c/em\u003e, \u003cem\u003erpl10\u003c/em\u003e, \u003cem\u003erpl16\u003c/em\u003e and \u003cem\u003erps3\u003c/em\u003e) was extracted. The dataset comprised six Ranunculaceae, two Menispermaceae, four Lauraceae, five Magnoliaceae, and three Nymphaeaceae species, with \u003cem\u003eCastanopsis carlesii\u003c/em\u003e and \u003cem\u003eQuercus acutissima\u003c/em\u003e (Fagaceae) as outgroups. Shared gene sequences were aligned and concatenated using MAFFT in PhyloSuite v1.2.3, and refined with Gblocks [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The final alignment was analyzed in IQ-TREE v1.6.8 [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], with ModelFinder selecting GTR\u0026thinsp;+\u0026thinsp;I+G as the best-fit model, and a maximum likelihood phylogeny was inferred from 1,000 bootstrap replicates. The tree was visualized using iTOL v6 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://itol.embl.de/\u003c/span\u003e\u003cspan address=\"https://itol.embl.de/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eStructural Features and Composition of\u003c/b\u003e \u003cb\u003eS. epigaea\u003c/b\u003e \u003cb\u003eOrganelle Genomes\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe identified seven contigs associated with the mitochondrial genome of \u003cem\u003eS. epigaea\u003c/em\u003e. These contigs have a total length of 466,726 bp and an average depth of 103.4x, resulting in four distinct conformations (chr1, chr2, chr3, chr4). Among these, chr2, chr3, and chr4 are circular, while chr1 exhibits a mixed structure comprising both circular and linear forms, with the linear contig2 connecting the circular contigs 1 and 3(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). For the conformation of chr1, we hypothesize a possible connection method: by duplicating contig2 and combining it with contig1 and contig3 to form a circular structure, where the duplicated contig2\u0026thinsp;+\u0026thinsp;and contig2- are reverse complementary sequences(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).In accordance with this hypothesis, we developed four PCR primers at the junctions of the overlapping regions (p1, p2, p3, and p4) to validate mitochondrial structure(Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Four clear and bright bands were obtained by PCR amplification and 1% agarose gel electrophoresis, these bands are consistent in size with the expected bands and sanger sequencing confirmed this connection(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe complete mitochondrial genome of \u003cem\u003eS. epigaea\u003c/em\u003e is 476,231 bp with a GC content of 47.0%. We annotated a total of 64 genes, which include 41 protein-coding genes (PCGs), 20 transfer RNAs (tRNAs), and 3 ribosomal RNAs (rRNAs). The PCGs comprise five subunits of ATPase (\u003cem\u003eatp1\u003c/em\u003e, \u003cem\u003eatp4\u003c/em\u003e, \u003cem\u003eatp6\u003c/em\u003e, \u003cem\u003eatp8\u003c/em\u003e, \u003cem\u003eatp9\u003c/em\u003e), four components involved in cytochrome c biogenesis (\u003cem\u003eccmB\u003c/em\u003e, \u003cem\u003eccmC\u003c/em\u003e, \u003cem\u003eccmFC\u003c/em\u003e, \u003cem\u003eccmFN\u003c/em\u003e), one apocytochrome b (\u003cem\u003ecob\u003c/em\u003e), three subunits of cytochrome c oxidase (\u003cem\u003ecox1\u003c/em\u003e, \u003cem\u003ecox2\u003c/em\u003e, \u003cem\u003ecox3\u003c/em\u003e), one maturase R (\u003cem\u003ematR\u003c/em\u003e), one transport membrane protein (\u003cem\u003emttB\u003c/em\u003e), nine subunits of NADH dehydrogenase (\u003cem\u003enad1\u003c/em\u003e, \u003cem\u003enad2\u003c/em\u003e, \u003cem\u003enad3\u003c/em\u003e, \u003cem\u003enad4\u003c/em\u003e, \u003cem\u003enad4L\u003c/em\u003e, \u003cem\u003enad5\u003c/em\u003e, \u003cem\u003enad6\u003c/em\u003e, \u003cem\u003enad7\u003c/em\u003e, \u003cem\u003enad9\u003c/em\u003e), 11 small subunits of the ribosome (\u003cem\u003erps1\u003c/em\u003e, \u003cem\u003erps10\u003c/em\u003e, \u003cem\u003erps11\u003c/em\u003e, \u003cem\u003erps12\u003c/em\u003e, \u003cem\u003erps13\u003c/em\u003e, \u003cem\u003erps14\u003c/em\u003e, \u003cem\u003erps19\u003c/em\u003e, \u003cem\u003erps2\u003c/em\u003e, \u003cem\u003erps3\u003c/em\u003e, \u003cem\u003erps4\u003c/em\u003e, \u003cem\u003erps7\u003c/em\u003e), four large subunits of the ribosome (\u003cem\u003erpl10\u003c/em\u003e, \u003cem\u003erpl16\u003c/em\u003e, \u003cem\u003erpl2\u003c/em\u003e, \u003cem\u003erpl5\u003c/em\u003e), and two subunits of succinate dehydrogenase(\u003cem\u003esdh3\u003c/em\u003e, \u003cem\u003esdh4\u003c/em\u003e). In addition, nine intron-containing genes, namely \u003cem\u003eccmFC\u003c/em\u003e, \u003cem\u003ecox2\u003c/em\u003e, \u003cem\u003enad1\u003c/em\u003e, \u003cem\u003enad2\u003c/em\u003e, \u003cem\u003enad4\u003c/em\u003e, \u003cem\u003enad5\u003c/em\u003e, \u003cem\u003enad7\u003c/em\u003e, \u003cem\u003erps10\u003c/em\u003e, and \u003cem\u003erps3\u003c/em\u003e, were identified in the mitochondrial genome. It is noteworthy that within the \u003cem\u003eccmFN\u003c/em\u003e gene, the premature appearance of a stop codon due to a base deletion has led to its annotation as a pseudogene (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe complete chloroplast genome of \u003cem\u003eS. epigaea\u003c/em\u003e is 158,139 bp with a GC content of 38.3%, exhibiting a typical quadripartite structure. The cpDNA comprises a Large Single Copy (LSC) region of 88,835 bp, a Small Single Copy (SSC) region of 19,796 bp, and two Inverted Repeats (IRs) regions of 24,754 bp each. We annotated a total of 130 genes, comprising 85 PCGs, 37 rRNA, and 8 tRNA. Among these genes, 17 are characterized by the presence of introns, with both \u003cem\u003eycf3\u003c/em\u003e and \u003cem\u003eclpP\u003c/em\u003e containing two introns each. The remaining 15 genes\u0026mdash;\u003cem\u003etrnK-UUU\u003c/em\u003e, \u003cem\u003erps16\u003c/em\u003e, \u003cem\u003etrnG-UCC\u003c/em\u003e, \u003cem\u003eatpF\u003c/em\u003e, \u003cem\u003erpoC1\u003c/em\u003e, \u003cem\u003etrnL-UAA\u003c/em\u003e, \u003cem\u003etrnV-UAC\u003c/em\u003e, \u003cem\u003epetB\u003c/em\u003e, \u003cem\u003epetD\u003c/em\u003e, \u003cem\u003erpl16\u003c/em\u003e, \u003cem\u003erpl2\u003c/em\u003e, \u003cem\u003endhB\u003c/em\u003e, \u003cem\u003etrnI-GAU\u003c/em\u003e, \u003cem\u003etrnA-UGC\u003c/em\u003e, and \u003cem\u003endhA\u003c/em\u003e each possess a single intron(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eList of genes encoded by the mtDNA of\u003c/b\u003e \u003cb\u003eS. epigaea\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup of genes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eName of genes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubunit of ATPase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eatp1\u003c/em\u003e, \u003cem\u003eatp4\u003c/em\u003e, \u003cem\u003eatp6\u003c/em\u003e, \u003cem\u003eatp8\u003c/em\u003e, \u003cem\u003eatp9(\u0026times;2)\u003c/em\u003e,\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCytochrome c biogenesis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eccmB\u003c/em\u003e, \u003cem\u003eccmC\u003c/em\u003e, \u003cem\u003eccmFC*\u003c/em\u003e, \u003cem\u003e#ccmFN\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApocytochrome b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ecob\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubunit of cytochrome c oxidase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ecox1\u003c/em\u003e, \u003cem\u003ecox2*\u003c/em\u003e, \u003cem\u003ecox3\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaturase R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ematR\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransport membrane protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003emttB\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubunit of NADH dehydrogenase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003enad1****\u003c/em\u003e, \u003cem\u003enad2****\u003c/em\u003e, \u003cem\u003enad3\u003c/em\u003e, \u003cem\u003enad4***\u003c/em\u003e, \u003cem\u003enad4L\u003c/em\u003e, \u003cem\u003enad5****\u003c/em\u003e, \u003cem\u003enad6\u003c/em\u003e, \u003cem\u003enad7****\u003c/em\u003e, \u003cem\u003enad9\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall subunit of ribosome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erps1\u003c/em\u003e, \u003cem\u003erps10\u003c/em\u003e, \u003cem\u003erps11\u003c/em\u003e, \u003cem\u003erps12\u003c/em\u003e, \u003cem\u003erps13\u003c/em\u003e, \u003cem\u003erps14\u003c/em\u003e, \u003cem\u003erps14(\u0026times;2)\u003c/em\u003e, \u003cem\u003erps19\u003c/em\u003e, \u003cem\u003erps2\u003c/em\u003e, \u003cem\u003erps3*\u003c/em\u003e, \u003cem\u003erps4\u003c/em\u003e, \u003cem\u003erps7\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarge subunit of ribosome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erpl10\u003c/em\u003e, \u003cem\u003erpl16\u003c/em\u003e, \u003cem\u003erpl2\u003c/em\u003e, \u003cem\u003erpl5\u003c/em\u003e, \u003cem\u003erpl5(\u0026times;2)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubunit of succinate dehydrogenase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003esdh3\u003c/em\u003e, \u003cem\u003esdh4\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRibosomal RNAs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrnL-CAA\u003c/em\u003e, \u003cem\u003etrnP-CGG*\u003c/em\u003e, \u003cem\u003etrnC-GCA\u003c/em\u003e, \u003cem\u003etrnD-GUC\u003c/em\u003e, \u003cem\u003etrnE-UUC\u003c/em\u003e, \u003cem\u003etrnE-UUC(\u0026times;2)\u003c/em\u003e, \u003cem\u003etrnF-GAA\u003c/em\u003e, \u003cem\u003etrnG-GCC\u003c/em\u003e, \u003cem\u003etrnH-GUG\u003c/em\u003e, \u003cem\u003etrnK-UUU\u003c/em\u003e, \u003cem\u003etrnM-CAU\u003c/em\u003e, \u003cem\u003etrnI-CAU\u003c/em\u003e, \u003cem\u003etrnfM-CAU\u003c/em\u003e, \u003cem\u003etrnN-GUU\u003c/em\u003e, \u003cem\u003etrnN-GUU(\u0026times;2)\u003c/em\u003e, \u003cem\u003etrnP-UGG\u003c/em\u003e, \u003cem\u003etrnP-UGG(\u0026times;2)\u003c/em\u003e, \u003cem\u003etrnQ-UUG\u003c/em\u003e, \u003cem\u003etrnS-GCU\u003c/em\u003e, \u003cem\u003etrnS-UGA\u003c/em\u003e, \u003cem\u003etrnT-GGU\u003c/em\u003e, \u003cem\u003etrnW-CCA\u003c/em\u003e, \u003cem\u003etrnY-GUA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransfer RNAs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003errn18\u003c/em\u003e, \u003cem\u003errn26\u003c/em\u003e, \u003cem\u003errn5\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eNote: *:intron number;#Gene:Pseudo gene;Gene(\u0026times;2):Number of copies of multi-copy genes\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eList of genes encoded by the cpDNA of\u003c/b\u003e \u003cb\u003eS. epigaea\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory of genes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroup of genes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eName of genes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGenes for photosynthesis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubunits of ATP synthase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eatpA\u003c/em\u003e, \u003cem\u003eatpB\u003c/em\u003e, \u003cem\u003eatpE\u003c/em\u003e, \u003cem\u003eatpF*\u003c/em\u003e, \u003cem\u003eatpH\u003c/em\u003e, \u003cem\u003eatpI\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubunits of NADH-dehydrogenase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003endhA*\u003c/em\u003e, \u003cem\u003endhB\u003c/em\u003e(\u0026times;2), \u003cem\u003endhC\u003c/em\u003e, \u003cem\u003endhD\u003c/em\u003e, \u003cem\u003endhE\u003c/em\u003e, \u003cem\u003endhF\u003c/em\u003e, \u003cem\u003endhG\u003c/em\u003e, \u003cem\u003endhH\u003c/em\u003e, \u003cem\u003endhI\u003c/em\u003e, \u003cem\u003endhJ\u003c/em\u003e, \u003cem\u003endhK\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubunits of cytochrome b/f complex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003epetA*\u003c/em\u003e, \u003cem\u003epetB*\u003c/em\u003e, \u003cem\u003epetD*\u003c/em\u003e, \u003cem\u003epetG\u003c/em\u003e, \u003cem\u003epetL\u003c/em\u003e, \u003cem\u003epetN\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubunits of photosystem Ⅰ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003epsaA\u003c/em\u003e, \u003cem\u003epsaB\u003c/em\u003e, \u003cem\u003epsaC\u003c/em\u003e, \u003cem\u003epsaI\u003c/em\u003e, \u003cem\u003epsaJ\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubunits of photosystem Ⅱ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003epsbA\u003c/em\u003e, \u003cem\u003epsbB\u003c/em\u003e, \u003cem\u003epsbC\u003c/em\u003e, \u003cem\u003epsbD\u003c/em\u003e, \u003cem\u003epsbE\u003c/em\u003e, \u003cem\u003epsbF\u003c/em\u003e, \u003cem\u003epsbH\u003c/em\u003e, \u003cem\u003epsbI\u003c/em\u003e, \u003cem\u003epsbJ\u003c/em\u003e, \u003cem\u003epsbK\u003c/em\u003e, \u003cem\u003epsbL\u003c/em\u003e, \u003cem\u003epsbM\u003c/em\u003e, \u003cem\u003epsbN\u003c/em\u003e, \u003cem\u003epsbT\u003c/em\u003e, \u003cem\u003epsbZ\u003c/em\u003e, \u003cem\u003eycf3**\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubunit of rubisco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003erbcL\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSelf-replication\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLarge subunit of ribosome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003erpl14\u003c/em\u003e, \u003cem\u003erpl16*\u003c/em\u003e, \u003cem\u003erpl2\u003c/em\u003e(\u0026times;2)\u003cem\u003e*\u003c/em\u003e, \u003cem\u003erpl20\u003c/em\u003e, \u003cem\u003erpl22\u003c/em\u003e, \u003cem\u003erpl23\u003c/em\u003e(\u0026times;2), \u003cem\u003erpl32\u003c/em\u003e, \u003cem\u003erpl33\u003c/em\u003e, \u003cem\u003erpl36\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edependent RNA polymerase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003erpoA\u003c/em\u003e, \u003cem\u003erpoB\u003c/em\u003e, \u003cem\u003erpoC1*\u003c/em\u003e, \u003cem\u003erpoC2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSmall subunit of ribosome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003erps11\u003c/em\u003e, \u003cem\u003erps12\u003c/em\u003e(\u0026times;2)\u003cem\u003e**\u003c/em\u003e, \u003cem\u003erps14\u003c/em\u003e, \u003cem\u003erps15\u003c/em\u003e, \u003cem\u003erps16*\u003c/em\u003e, \u003cem\u003erps18\u003c/em\u003e, \u003cem\u003erps19\u003c/em\u003e, \u003cem\u003erps2\u003c/em\u003e, \u003cem\u003erps3\u003c/em\u003e, \u003cem\u003erps4\u003c/em\u003e, \u003cem\u003erps7\u003c/em\u003e(\u0026times;2), \u003cem\u003erps8\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003etRNA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003etRNA genes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003etrnH-GUG\u003c/em\u003e, \u003cem\u003etrnK-UUU*\u003c/em\u003e, \u003cem\u003etrnQ-UUG\u003c/em\u003e, \u003cem\u003etrnS-GCU\u003c/em\u003e, \u003cem\u003etrnG-UCC*\u003c/em\u003e, \u003cem\u003etrnR-UCU\u003c/em\u003e, \u003cem\u003etrnC-GCA\u003c/em\u003e, \u003cem\u003etrnD-GUC\u003c/em\u003e, \u003cem\u003etrnY-GUA\u003c/em\u003e, \u003cem\u003etrnE-UUC\u003c/em\u003e, \u003cem\u003etrnT-GGU\u003c/em\u003e, \u003cem\u003etrnS-UGA\u003c/em\u003e, \u003cem\u003etrnG-GCC\u003c/em\u003e, \u003cem\u003etrnfM-CAU\u003c/em\u003e, \u003cem\u003etrnS-GGA\u003c/em\u003e, \u003cem\u003etrnT-UGU\u003c/em\u003e, \u003cem\u003etrnL-UAA*\u003c/em\u003e, \u003cem\u003etrnF-GAA\u003c/em\u003e, \u003cem\u003etrnV-UAC*\u003c/em\u003e, \u003cem\u003etrnM-CAU\u003c/em\u003e, \u003cem\u003etrnW-CCA\u003c/em\u003e, \u003cem\u003etrnP-UGG\u003c/em\u003e, \u003cem\u003etrnI-CAU\u003c/em\u003e, \u003cem\u003etrnL-CAA\u003c/em\u003e, \u003cem\u003etrnV-GAC\u003c/em\u003e, \u003cem\u003etrnA-UGC*\u003c/em\u003e, \u003cem\u003etrnR-ACG\u003c/em\u003e, \u003cem\u003etrnN-GUU\u003c/em\u003e, \u003cem\u003etrnL-UAG\u003c/em\u003e, \u003cem\u003etrnN-GUU\u003c/em\u003e(\u0026times;2), \u003cem\u003etrnR-ACG\u003c/em\u003e(\u0026times;2), \u003cem\u003etrnA-UGC\u003c/em\u003e(\u0026times;2)*, \u003cem\u003etrnI-GAU\u003c/em\u003e(\u0026times;2)*, \u003cem\u003etrnV-GAC\u003c/em\u003e(\u0026times;2), \u003cem\u003etrnL-CAA\u003c/em\u003e(\u0026times;2), \u003cem\u003etrnI-CAU\u003c/em\u003e(\u0026times;3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003erRNA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003erRNA genes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003errn16S\u003c/em\u003e(\u0026times;2), \u003cem\u003errn23S\u003c/em\u003e(\u0026times;2), \u003cem\u003errn4.5S\u003c/em\u003e(\u0026times;2), \u003cem\u003errn5S\u003c/em\u003e(\u0026times;2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOther genes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubunit of Acetyl-CoA-carboxylase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eaccD\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC-type cytochrom synthesis gene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eccsA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnvelop membrane protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ecemA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProtease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eclpP**\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaturase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ematK\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTranslational initiation factor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003einfA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUnkown\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConserved open reading frames\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eycf1\u003c/em\u003e, \u003cem\u003eycf2\u003c/em\u003e(\u0026times;2), \u003cem\u003eycf4\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: Genes with one or two introns are indicated by one (*) or two asterisks (**). Genes with two copies are denoted by (x2).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eRepeat sequence analysis\u003c/h2\u003e \u003cp\u003eSimple sequence repeats (SSRs), also known as microsatellite DNA, are tandemly repeated sequences composed of 1\u0026ndash;6 nucleotides and are widely distributed throughout eukaryotic genomes [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In this study, we detected 134 and 68 SSRs in mtDNA and cpDNA, respectively. The SSRs in mtDNA are primarily composed of monomeric and tetrameric repeats, accounting for 62.69% (84) of the total SSRs. In cpDNA, the SSRs are predominantly monomeric, accounting for 72.06% (49) of the total.\u003c/p\u003e \u003cp\u003eTandem repeats with longer repeat units, commonly referred to as satellite DNA, consist of repeated sequences that are typically longer than SSRs(Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). In the mitochondrial and chloroplast genomes of \u003cem\u003eS. epigaea\u003c/em\u003e, 21 and 42 tandem repeat sequences were detected, respectively, along with 90 pairs and 29 pairs of dispersed repeat sequences (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). Among these, the mitochondrial genome contains 41 forward repeats (F) and 49 palindromic repeats (P), while the chloroplast genome includes 14 forward repeats (F), 14 palindromic repeats (P), and one reverse repeat (R). Neither genome exhibited complementary repeats (C).In the mitochondrial genome, the longest forward repeat identified was 332 bp, whereas the longest palindromic repeat was 9,506 bp(Table S4). In contrast, in the chloroplast genome, the longest forward repeat identified was 39 bp, whereas the longest palindromic repeat was 24,754 bp(Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCodon usage analysis among PCGs\u003c/h2\u003e \u003cp\u003eIn the analysis of organelle genomes, the relative synonymous codon usage (RSCU) is frequently calculated to assess codon usage bias. In mtDNA, RSCU values range from 1.560 for GCT in alanine to 0.487 for TAC in tyrosine. Conversely, in cpDNA, RSCU values vary from 1.774 for TTA in leucine to 0.378 for CTC in leucine. Statistical analysis indicates that in the mt genome, there are 30 codons with RSCU values exceeding 1, while 32 codons have values below 1. In cpDNA, 31 codons exhibit RSCU values greater than 1, and 31 codons fall below this threshold. This suggests that the mtDNA may be subject to stronger mutational pressures, resulting in a slightly higher frequency of low-frequency codons, whereas the cpDNA experiences relatively balanced selective and mutational pressures. Notably, the RSCU values for TGG in tryptophan and ATG in methionine are both equal to 1, indicating that there is no codon usage bias for these codons (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB; Table S5).\u003c/p\u003e \u003cp\u003eENC-plot analysis demonstrates that most genes in \u003cem\u003eS. epigaea\u003c/em\u003e organelle genomes fall below theoretical expectations, indicating codon usage bias is shaped by natural selection rather than GC\u003csub\u003e3\u003c/sub\u003e content alone. Notably, in mitochondria, the \u003cem\u003eatp4\u003c/em\u003e, \u003cem\u003erps7\u003c/em\u003e and \u003cem\u003erps4\u003c/em\u003e genes deviate from the standard curve, while in chloroplasts, the \u003cem\u003erpl14\u003c/em\u003e and \u003cem\u003endhJ\u003c/em\u003e genes also exhibit significant deviations from the standard curve(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD; Table S6). It is speculated that these genes have undergone strong selection during evolution, favoring the use of specific synonymous codons.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eHorizontal gene transfer of\u003c/b\u003e \u003cb\u003eS. epigaea\u003c/b\u003e \u003cb\u003eorganelle genomes\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIntracellular gene transfer (IGT) is a pivotal mechanism driving eukaryotic evolution, through BLASTn analysis of the organelle genomes, we identified 24 homologous sequences, encompassing both genes and intergenic regions(Table S7 and Table S8). The lengths of these sequences range from 28 to 1,233 bp, with a cumulative length of 9,558 bp, which constitutes 6.04% of the chloroplast genome. We annotated these homologous sequences and found that four are fragments of chloroplast genes \u003cem\u003e(psbD\u003c/em\u003e, \u003cem\u003endhB\u003c/em\u003e, \u003cem\u003epetL\u003c/em\u003e, \u003cem\u003epetG\u003c/em\u003e), along with nine complete tRNAs (\u003cem\u003etrnD-GUC\u003c/em\u003e, \u003cem\u003etrnT-GGU\u003c/em\u003e, \u003cem\u003etrnM-CAU\u003c/em\u003e, \u003cem\u003etrnW-CCA\u003c/em\u003e, \u003cem\u003etrnP-UGG\u003c/em\u003e, \u003cem\u003etrnI-CAU\u003c/em\u003e, \u003cem\u003etrnN-GUU\u003c/em\u003e, \u003cem\u003etrnA-UGC\u003c/em\u003e, \u003cem\u003etrnI-CAU\u003c/em\u003e), and two complete rRNAs (\u003cem\u003errn4.5S\u003c/em\u003e, \u003cem\u003errn23S\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). These findings substantiate the occurrence of DNA transfer from chloroplasts to mitochondria in \u003cem\u003eS. epigaea\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRNA editing sites\u003c/h2\u003e \u003cp\u003eA total of 672 potential RNA editing sites were identified in the \u003cem\u003eS. epigaea\u003c/em\u003e mitogenome (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). All RNA editing sites predicted were C to U (T) base editing (Table S9). The gene \u003cem\u003enad\u003c/em\u003e4 encodes the most RNA editing sites, with 52 RNA editing sites identified, followed by the gene \u003cem\u003eccmB\u003c/em\u003e with 40 RNA editing events; the gene \u003cem\u003esdh3\u003c/em\u003e genes had only one potential RNA editing event. Remarkably, the \u003cem\u003eatp1\u003c/em\u003e genes displayed no editing sites. After RNA editing, some changes occur in the properties of the original amino acids, 48.07% of the amino acids were predicted to change from hydrophilic to hydrophobic, while 8.33% were predicted to change from hydrophobic to hydrophilic. It was also found three genes (\u003cem\u003eatp6\u003c/em\u003e, \u003cem\u003eatp9\u003c/em\u003e and \u003cem\u003erps11\u003c/em\u003e) exhibit altered open reading frames due to RNA editing, which results in the production of a termination codon. Additionally, we find amino acids predicted to edit codons show a leucine bias after RNA editing, this is supported by the fact that 42.86% (288 sites) of the amino acids were converted to leucine (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrediction of RNA editing sites\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRNA -editing\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"11\" rowspan=\"12\"\u003e \u003cp\u003ehydrophobic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCA (A)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;GUA (V)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"11\" rowspan=\"12\"\u003e \u003cp\u003e29.76%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCG (A)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;GUG (V)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCU (A)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;GUU (V)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCC (A)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;GUC (V)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCUC (L)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UUC (F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCUU (L)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UUU (F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCA (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;CUA (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCC (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;CUC (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCU (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UUU (F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCC (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UUC (F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCG (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;CUG (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCU (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;CUU (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003ehydrophilic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCGC (R)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UGC (C)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e13.39%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCGU (R)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UGU (C)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAU (H)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UAU (Y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAC (H)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UAC (Y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003ehydrophobic-hydrophilic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCA (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UCA (S)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e8.33%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCC (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UCC (S)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCG (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UCG (S)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCU (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UCU (S)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003ehydrophilic-hydrophobic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCGG (R)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UGG (W)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003e48.07%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUCA (S)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UUA (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUCC (S)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UUC (F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUCG (S)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UUG (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUCU (S)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UUU (F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eACA (U)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;AUA (I)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eACC (U)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;AUC (I)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eACU (U)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;AUU (I)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eACG (U)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;AUG (M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ehydrophilic-stop\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCGA (R)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UGA (X)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.45%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAA (Q)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;UAA (X)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eKa/Ks analyses\u003c/h2\u003e \u003cp\u003eTo assess environmental stress effects on mitochondrial genome evolution, Ka/Ks ratios were calculated for 20 conserved protein-coding genes (PCGs) across \u003cem\u003eS. epigaea\u003c/em\u003e, \u003cem\u003eS. japonica\u003c/em\u003e, \u003cem\u003eAconitum kusnezoffii\u003c/em\u003e, \u003cem\u003eClematis dilatata\u003c/em\u003e, and \u003cem\u003ePulsatilla chinensis\u003c/em\u003e After calculation, the Ka/Ks values of most PCGs in the mitochondrial genome of \u003cem\u003eS. epigaea\u003c/em\u003e are less than 1 suggests that most genes tend to maintain their original function and avoid deleterious mutations. It is noteworthy that some genes exhibit signs of positive selection (Ka/Ks\u0026thinsp;\u0026gt;\u0026thinsp;1), including the \u003cem\u003enad2\u003c/em\u003e, \u003cem\u003enad4\u003c/em\u003e, and \u003cem\u003erps4\u003c/em\u003e genes, suggests that the gene may be undergoing adaptive changes(Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e; Table S10).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003ePhylogenetic and collinearity analyses\u003c/h2\u003e \u003cp\u003eTo ascertain the phylogenetic position of \u003cem\u003eS. epigaea\u003c/em\u003e within \u003cem\u003eStephania\u003c/em\u003e, we constructed a maximum likelihood (ML) phylogeny based on 20 shared mitochondrial protein-coding genes (PCGs) across 21 species (Table S11). The dataset included representatives from five families (Ranunculaceae, Menispermaceae, Lauraceae, Magnoliaceae, Nymphaeaceae), with \u003cem\u003eCastanopsis carlesii\u003c/em\u003e and \u003cem\u003eQuercus acutissima\u003c/em\u003e (Fagaceae) as outgroups. ModelFinder identified GTR\u0026thinsp;+\u0026thinsp;I+G as the best-fitting model for the concatenated matrix. Notably, 88% of nodes received bootstrap support\u0026thinsp;\u0026ge;\u0026thinsp;90%, including 13 nodes with 100% support. (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). The structure of the mitochondrial DNA phylogenetic tree aligns with the most recent taxonomic framework established by the Angiosperm Phylogeny Group (APG). \u003cem\u003eS. epigaea\u003c/em\u003e clustered with species from the Menispermaceae family, forming a subclade that includes \u003cem\u003eS. japonica\u003c/em\u003e, which is consistent with our expectations.\u003c/p\u003e \u003cp\u003eTo explore the homology of mitochondrial genomes between \u003cem\u003eS. epigaea\u003c/em\u003e and its closely related species, we conducted pairwise comparisons of the mitochondrial genomes of \u003cem\u003eS. epigaea\u003c/em\u003e with the congeneric species \u003cem\u003eS. japonica\u003c/em\u003e and three species from the Ranunculaceae family using the Blastn, while excluding blocks shorter than 0.5 kb (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e; Table S12). The results indicated that there are numerous homologous collinearity blocks and inversion blocks between \u003cem\u003eS. epigaea\u003c/em\u003e and its closely related species (\u003cem\u003eS. japonica\u003c/em\u003e), with the maximum block length being 29,498 bp and a collinearity value of 98.36%, this indicated that the mitochondrial genomes of \u003cem\u003eS. epigaea\u003c/em\u003e and \u003cem\u003eS. japonica\u003c/em\u003e are relatively conserved and exhibit a close phylogenetic relationship. In contrast, the number of homologous collinear blocks between \u003cem\u003eS. epigaea\u003c/em\u003e and \u003cem\u003eClematis dilatata\u003c/em\u003e is relatively low, and the lengths of these blocks are shorter, with a significant presence of unaligned sequence gaps. Compared to Ranunculaceae, this indicated that the \u003cem\u003eS. epigaea\u003c/em\u003e mitochondrial genome has undergone extensive rearrangements, which leading to a differentiation in their phylogenetic relationships.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eComparative Organelle Genomics: Structure and Features\u003c/h2\u003e \u003cp\u003eMitochondria are essential ATP-generating organelles in most eukaryotic cells, powering cellular processes through oxidative phosphorylation and thus designated as cellular \"powerhouses\" [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Similarly, chloroplasts are analogous energy-transducing organelles in plant cells that convert solar energy into carbohydrates via photosynthesis, thereby fueling plant growth and development [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Studies of plant organelle genomes elucidate the evolutionary mechanisms of energy metabolism pathways and reveal the genetic basis of organelle functional divergence, providing insights into plant adaptive evolution [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Although plant mitochondrial genomes are typically depicted as circular molecules, their actual structures can vary, including linear conformations (\u003cem\u003eQuercus acutissima\u003c/em\u003e) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], branched conformations (A\u003cem\u003ebelmoschus esculentus\u003c/em\u003e) [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], multicyclic structures (\u003cem\u003eAngelica dahurica\u003c/em\u003e) [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], and complex structures (\u003cem\u003ePanax notoginseng\u003c/em\u003e) [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Additionally, different mitochondrial conformations may also arise at various developmental stages of the plant (\u003cem\u003eLactuca sativa\u003c/em\u003e) [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. In our study, the mitochondrial genome of \u003cem\u003eS. epigaea\u003c/em\u003e exhibits a simpler architecture, characterized by three circular structures and one hybrid structure. This finding starkly contrasts with the complex multi-ring architecture observed in its congener, \u003cem\u003eS. japonica\u003c/em\u003e [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Visualization and analysis using Bandage software revealed that this hybrid structure can be reassembled into a circular form through the duplication of shared sequences.; its disassembly process resembles that of the mitochondrial genome of \u003cem\u003eCyperus stoloniferus\u003c/em\u003e [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. The authenticity of this structure was confirmed through PCR amplification and sequencing of the overlapping regions. In contrast to this relatively simple structure, many more complex architectures are found in the mitochondria of other species. For example, the mitochondrial genome of \u003cem\u003ePanax notoginseng\u003c/em\u003e exhibits a more intricate structure, containing multiple repeating regions and circular forms [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Multi-circular phenomena are also prevalent in plant mitochondria; for instance, the mitochondrial genome of \u003cem\u003eAngelica dahurica\u003c/em\u003e comprises 12 circular structures, while that of \u003cem\u003ePunica granatum\u003c/em\u003e consists of 7 circular structures. These varying structures highlight the diversity and complexity of plant mitochondrial genomes.In contrast to mitochondrial genomes, chloroplast genomes typically exhibit a highly conserved structure and a relatively stable genome size. They form a quadripartite circular structure composed of a small single-copy region (SSC), a large single-copy region (LSC), and two inverted repeat regions (IRs). The chloroplast genome of \u003cem\u003eS. epigaea\u003c/em\u003e exhibits a typical quadripartite conformation, with a size of 158,139 bp comparable to that of its closely related species, \u003cem\u003eStephania yunnanensis\u003c/em\u003e (NC_087726, 158,146 bp) and \u003cem\u003eStephania cephalantha\u003c/em\u003e (NC_067079, 158,052 bp). Overall, mitochondrial genomes exhibit greater complexity than chloroplast genomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eCodon Usage Divergence\u003c/h2\u003e \u003cp\u003eCodons serve as the bridge between nucleic acids and proteins in translating genetic information, reflecting the dynamic balance between natural selection and mutational bias [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. RSCU analysis reveals that the chloroplast genome of \u003cem\u003eS. epigaea\u003c/em\u003e contains a total of 30 codons with RSCU values exceeding 1, while the mitochondrial genome comprises 28 such codons. Notably, most codons end with A or U, reflecting a preference common in many plant species that is typically associated with abundant tRNA populations. Preferential use of A/U-ending codons in \u003cem\u003eS. epigaea\u003c/em\u003e organelles enhances codon-tRNA binding efficiency, minimizes ribosomal pausing, and improves translational efficiency [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Additionally, a certain number of mutations may have accumulated in the organellar genomes of \u003cem\u003eS. epigaea\u003c/em\u003e during evolution, and the A/U preference can compensate for the negative effects of these mutations by enhancing RNA editing efficiency. RNA editing often occurs in A/U-enriched regions, and the large number of A/U-ending codons in the organelles of \u003cem\u003eS. epigaea\u003c/em\u003e can provide more editing sites. Post-transcriptional modifications can correct the coding errors caused by mutations, ensuring the accuracy of protein sequences [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eENC analysis indicates that the codon usage bias of the organellar genes in \u003cem\u003eS. epigaea\u003c/em\u003e is generally weak. In our study, the chloroplast genome ENC values ranged from 38.39\u0026ndash;56.37 (mean 48.62), whereas mitochondrial genome values exhibited a broader range (39.17\u0026ndash;61.00, mean 52.73), with all genes showing weak codon usage bias (ENC\u0026thinsp;\u0026gt;\u0026thinsp;35). Notably, the average ENC of the mitochondria is significantly higher than that of the chloroplasts, suggesting that its codon usage is less constrained by natural selection, which may be related to the unique regulatory mechanisms of mitochondrial gene expression. The ENC-GC\u003csub\u003e3\u003c/sub\u003e curve is a tool used to analyze codon usage preferences. ENC-GC\u003csub\u003e3\u003c/sub\u003e curve analysis reveals codon usage variation among genes, enabling inference of evolutionary relationships and selective pressures [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. ENC-plot analysis reveals similarities in the regulatory mechanisms of codon usage preferences between the chloroplast and mitochondrial genomes of \u003cem\u003eS. epigaea\u003c/em\u003e. Most genes are situated below the neutral curve of the ENC theory, indicating that their codon usage bias is regulated by both mutation and natural selection, with natural selection being the dominant factor. This finding aligns with the functional requirements of organelles: natural selection enhances the expression efficiency of core functional genes through the directional optimization of codon usage patterns, thereby ensuring the efficient progression of photosynthesis in chloroplasts and energy metabolism in mitochondria [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Notably, the ENC values of the mitochondrial genes \u003cem\u003eatp4\u003c/em\u003e, \u003cem\u003erps7\u003c/em\u003e, and \u003cem\u003erps4\u003c/em\u003e, as well as the chloroplast genes \u003cem\u003erpl14\u003c/em\u003e and \u003cem\u003endhJ\u003c/em\u003e, are significantly higher than the expected values according to the theoretical curve. This observation suggests that these genes may have undergone directional codon optimization [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eHorizontal gene transfer between chloroplast and mitochondrial genomes\u003c/h2\u003e \u003cp\u003eHorizontal gene transfer (HGT) is a pivotal mechanism driving eukaryotic evolution, facilitating genetic recombination and functional integration among cells and organelles [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. In this analysis, we identified 24 homologous fragments between the mitochondrial and chloroplast genomes of \u003cem\u003eS. epigaea\u003c/em\u003e, ranging in size from 28 to 1,233 bp. The total length of these fragments is 9,588 bp, which constitutes 6.04% of the chloroplast genome length and 2.01% of the mitochondrial genome length. This proportion is significantly higher than that of its congener, \u003cem\u003eS. japonica\u003c/em\u003e(0.87%) [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].The largest fragment detected measured 1,233 bp in length and included two complete PCGs (\u003cem\u003epetL\u003c/em\u003e and \u003cem\u003epetG\u003c/em\u003e) as well as two complete tRNA genes (\u003cem\u003etrnW-CCA\u003c/em\u003e and \u003cem\u003etrnP-UGG\u003c/em\u003e), In addition, partial fragments of the \u003cem\u003endhB\u003c/em\u003e and \u003cem\u003epsbD\u003c/em\u003e genes, along with seven complete tRNA genes (\u003cem\u003etrnD-GUC\u003c/em\u003e, \u003cem\u003etrnT-GGU\u003c/em\u003e, \u003cem\u003etrnM-CAU\u003c/em\u003e, \u003cem\u003etrnI-CAU\u003c/em\u003e, \u003cem\u003etrnN-GUU\u003c/em\u003e, \u003cem\u003etrnA-UGC\u003c/em\u003e, and \u003cem\u003etrnI-CAU\u003c/em\u003e), have also been transferred. The results obtained for \u003cem\u003eS. epigaea\u003c/em\u003e in this study align with the previously reported tRNA transfer events observed in \u003cem\u003eS. japonica\u003c/em\u003e. The five tRNA genes (\u003cem\u003etrnM-CAU\u003c/em\u003e, \u003cem\u003etrnN-GUU\u003c/em\u003e, \u003cem\u003etrnI-CAU\u003c/em\u003e, \u003cem\u003etrnD-GUC\u003c/em\u003e, and \u003cem\u003etrnT-GGU\u003c/em\u003e) identified as transferred in \u003cem\u003eS. japonica\u003c/em\u003e are fully encompassed within the nine complete transferred tRNA genes found in \u003cem\u003eS. epigaea\u003c/em\u003e. This set of shared transferred tRNA genes suggests that HGT of these tRNA genes is a conserved evolutionary feature within the genus \u003cem\u003eStephania\u003c/em\u003e. These shared transferred tRNA genes represent a conserved HGT event within \u003cem\u003eStephania\u003c/em\u003e, reflecting common selective pressures or shared genomic mechanisms favoring retention of plastid-derived tRNAs in mitochondrial genomes.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRNA editing events in the mitochondrial genome of\u003c/b\u003e \u003cb\u003eS. epigaea\u003c/b\u003e\u003c/p\u003e \u003cp\u003eRNA editing denotes the addition, deletion, and substitution of bases at the RNA level, resulting in a nucleotide sequence that diverges from the genomic DNA sequence, so altering genetic information [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Analysis of RNA editing sites elucidates mitochondrial gene expression in plants. In our study, we identified 672 RNA editing sites in the \u003cem\u003eS. epigaea\u003c/em\u003e mitochondrial genome, both of which were C to U editing.The number of RNA editing sites in the mitochondrial genome of \u003cem\u003eS. epigaea\u003c/em\u003e is close to that of the closely related species \u003cem\u003eS. Japonica\u003c/em\u003e (684) [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], the most editing sites were \u003cem\u003enad4\u003c/em\u003e genes. However, \u003cem\u003eatp1\u003c/em\u003e genes were all failed to detect RNA editing sites.The editing sites of plant mitochondrial genes exhibit an evolutionary dynamic of \"gain-loss\". The editing site of the atp1 gene within the mitochondrial genome may lose its selective advantage due to DNA mutations, ultimately leading to its loss over evolutionary time [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe found that three genes (\u003cem\u003eatp\u003c/em\u003e6, \u003cem\u003eatp\u003c/em\u003e9 and \u003cem\u003erps\u003c/em\u003e11) exhibit altered open reading frames due to RNA editing, which results in the production of a termination codon. The generation of premature termination codons mediated by RNA editing is an important mechanism for regulating mitochondrial gene expression in plants. On the one hand, it may fine-tune mitochondrial function via truncated protein production [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]; on the other, it may function as a quality control mechanism that eliminates aberrant transcripts and prevents accumulation of defective full-length proteins [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].Furthermore, this phenomenon occurs simultaneously in the \u003cem\u003eatp6\u003c/em\u003e, \u003cem\u003eatp9\u003c/em\u003e, and \u003cem\u003erps11\u003c/em\u003e genes, suggesting that RNA editing may exert a synergistic regulatory effect on these three genes, collectively influencing mitochondrial energy metabolism and the translation process.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eThe Ka/Ks in the mitochondrial genome\u003c/h2\u003e \u003cp\u003eKa/Ks is an important indicator used in molecular evolution studies to measure the selective pressure on gene or protein-coding sequences [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e].The ka/ks analysis of \u003cem\u003eS. epigaea\u003c/em\u003e and its closely related species, including \u003cem\u003eS. japonica\u003c/em\u003e, \u003cem\u003eA. kusnezoffii\u003c/em\u003e, \u003cem\u003eC. dilatata\u003c/em\u003e, and \u003cem\u003eP. chinensis\u003c/em\u003e, indicates that most of the ka/ks values are less than 1. This suggests that nonsynonymous substitutions are subject to negative selection, wherein deleterious mutations are purged, thus preserving the stability of protein function [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Positive selection signatures (ka/ks\u0026thinsp;\u0026gt;\u0026thinsp;1) in \u003cem\u003enad2\u003c/em\u003e, \u003cem\u003erps4\u003c/em\u003e, \u003cem\u003enad4\u003c/em\u003e, and \u003cem\u003eatp6\u003c/em\u003e suggest retention of beneficial mutations driving adaptive protein evolution. Both \u003cem\u003enad2\u003c/em\u003e and \u003cem\u003enad4\u003c/em\u003e are essential genes encoded by the plant mitochondrial genome, and their products serve as key subunits of respiratory chain complex I. Variations in their amino acid sequences directly influence electron transfer efficiency, proton transmembrane transport capacity, and ATP synthesis rates [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. A Ka/Ks ratio greater than 1 suggests that these genes may have optimized the structural stability or functional efficiency of complex I, enabling \u003cem\u003eS. epigaea\u003c/em\u003e to exhibit enhanced adaptability in energy metabolism under specific habitats, such as drought and high temperatures. This optimization ensures the proper functioning of the mitochondrial respiratory chain and the stability of cellular energy metabolism.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study successfully sequenced and assembled the mitochondrial and chloroplast genomes of \u003cem\u003eS. epigaea\u003c/em\u003e, and verified the mitochondrial structures through PCR amplification. The mitochondrial genome (466,726 bp) comprises three circular chromosomes and one complex structure, while the chloroplast genome (158,139 bp) exhibits a typical quadripartite circular architecture. We analyzed the repetitive sequences of mitochondrial and chloroplast genomes of \u003cem\u003eS. epigaea\u003c/em\u003e, as well as the RSCU values, ENC-plot, and inter-organelle gene transfer. The comparative analysis of these two genomes enhances our understanding of the organelles in this species. We also conducted Ka/Ks analysis, collinearity analyses, and phylogenetic analysis of \u003cem\u003eS. epigaea\u003c/em\u003e using mitochondrial data from closely related species. The analyses indicate that \u003cem\u003eS. epigaea\u003c/em\u003e is most closely related to \u003cem\u003eS. japonica\u003c/em\u003e. These results will aid in understanding the organellar genomic characteristics of the \u003cem\u003eStephania\u003c/em\u003e genus, providing important data resources for the evolutionary studies, species identification, and genetic diversity of the \u003cem\u003eStephania\u003c/em\u003e plants.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.C., L.W. and G.L. conceived and designed the research. J.C. and C.Y. performed the experiments. Y.Z. and Q.M. contributed to data analysis and visualization. J.C. wrote the original draft. L.W. and G.L. reviewed and edited the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the 12th Five-year Key Construction Discipline of State Administration of Traditional Chinese Medicine \u0026quot;Dai Pharmacy\u0026quot;（2024SS24088、2024JS2407）\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe complete mitochondrial genome (GenBank accession: PX696013) and chloroplast genome (GenBank accession: PX712054) of \u003cem\u003eStephania epigaea\u003c/em\u003e are publicly available in GenBank.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1Yunnan Key Laboratory of Dai and Yi Medicines, Yunnan University of Chinese Medicine, Kunming, 650500, China.\u003c/p\u003e\n\u003cp\u003e2College of Chinese Material Medica, Yunnan University of Chinese Medicine, Kunming, 650500, China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLv J-J, Xu M, Wang D, Zhu H-T, Yang C-R, Wang Y-F, Li Y, Zhang Y-J: Cytotoxic Bisbenzylisoquinoline Alkaloids from \u003cem\u003eStephania epigaea\u003c/em\u003e. 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The Plant Cell 2010, 22(3):797-810.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Stephania epigaea, mitogenome, chloroplast, repeat sequence, RNA-editing site, phylogenetic relationships","lastPublishedDoi":"10.21203/rs.3.rs-8707172/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8707172/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMitochondria and chloroplast are central organelles in plant metabolism, playing crucial roles at various developmental stages. \u003cem\u003eStephania epigaea\u003c/em\u003e is a traditional medicinal plant utilized by minority ethnic groups, widely employed for treating malaria and stomach pain. Understanding the organelle genomes of \u003cem\u003eS. epigaea\u003c/em\u003e\u0026mdash;specifically its mitochondrial and chloroplast genomes\u0026mdash;is essential for elucidating the molecular strategies underlying this species' evolutionary adaptation. The complete mitochondrial genome of this species is 476,231 bp in length and comprises three discrete circular chromosomes together with one additional complex structure. In contrast, the chloroplast genome is 158,139 bp and exhibits the canonical circular quadripartite architecture. A homologous segment of 9,558 bp was found to be shared with the chloroplast, involving the migration 24 homologous sequences. Relative Synonymous Codon Usage (RSCU) analysis indicates that the codon preference in the chloroplast genome of \u003cem\u003eS. epigaea\u003c/em\u003e is generally higher than that in the mitochondria. Phylogenetic analysis indicates that \u003cem\u003eS. epigaea\u003c/em\u003e shares a close genetic relationship with the congeneric plant \u003cem\u003eS. japonica\u003c/em\u003e, and a substantial number of homologous blocks have been identified in the synteny analysis. Selection pressure analysis shows that the most of protein-coding genes (PCGs) exhibit a Ka/Ks ratio of less than 1, suggesting that these genes tend to maintain their original functions and avoid deleterious mutations. This study has significant implications for understanding the evolutionary relationships within the genus \u003cem\u003eStephania\u003c/em\u003e, laying a foundation for genetic research on the traditional medicine \u003cem\u003eS. epigaea\u003c/em\u003e.\u003c/p\u003e","manuscriptTitle":"Organellar Genome Analysis of Stephania epigaea: A Medicinal Plant Endemic to Southwest China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-26 17:26:38","doi":"10.21203/rs.3.rs-8707172/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-17T03:55:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"244803093498441617162963571049844066232","date":"2026-04-27T13:34:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-20T15:08:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"32266002640386609887683038999681784365","date":"2026-04-09T01:58:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-25T07:33:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-22T03:41:07+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-19T19:22:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-18T09:25:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Genomics","date":"2026-03-18T07:45:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c30b1c37-7432-4a7d-bca0-7aad7d30cc29","owner":[],"postedDate":"March 26th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-17T03:55:19+00:00","index":100,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-26T17:26:38+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-26 17:26:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8707172","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8707172","identity":"rs-8707172","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}