Comparative genomic and phylogenetic analyses of mitochondrial genomes of Graptopetalum paraguayense (N. E. Br.) Walth.1938

Comparative genomic and phylogenetic analyses of mitochondrial genomes of Graptopetalum paraguayense (N. E. Br.) Walth.1938 | 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 Article Comparative genomic and phylogenetic analyses of mitochondrial genomes of Graptopetalum paraguayense (N. E. Br.) Walth.1938 Xue Zhou, ChuQi Lin, ZhiRui Li, Lin Zhou, Xi Du This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7592618/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Jan, 2026 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract Graptopetalum paraguayense is a perennial succulent plant with ornamental value, functional value and medicinal activity. This study presents the first complete mitochondrial genome of G. paraguayense . We assembled and annotated the complete mitochondrial genome of G. paraguayense . we characterized a 242,059bp circular mitogenome with 43.65% GC content, harboring 50 functional genes (31 PCGs, 13 tRNAs, 3 rRNAs) and 3 pseudogenes. Identification of 599 RNA editing sites, predominantly altering amino acid hydrophobicity (47.41% hydrophilic-to-hydrophobic conversions). Codon usage bias analysis revealing preferential use of GCU (Ala), CGA (Arg), and UUA (Leu), with UAA stop codon exhibiting highest RSCU (1.9355). A total of 122 repetitive sequences were identified, including 59 Simple sequence repeat, 1 tandem repeat, and 62 dispersed repeat. Ka/Ks analysis indicating positive selection on ccm B and nad 7 genes. G. paraguayense shared 57.28% sequence similarity with Sedum plumbizincicola. Evidence of chloroplast-to-mitochondrial DNA transfer involving psa C, ndh E, ndh G, ndh I, ndh A, ndh H genes. Eleven divergent hotspot regions were identified by comparative analyses, were atp9 , atp 8, rpl 5, cox 2, ccm Fn, rps 7, ccm C, ccm Fc, mtt B, nad 6 and rps 13. Based on phylogenetic tree analysis, G. paraguayense is highly related to Sedum plumbizincicola. These results provide foundational insights into mitogenome evolution in Crassulaceae, highlighting adaptive genetic mechanisms and interorganellar gene transfer in succulent plants. Biological sciences/Biotechnology Biological sciences/Genetics Biological sciences/Molecular biology Biological sciences/Plant sciences Graptopetalum paraguayense Mitochondrial genome Phylogeny Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction Graptopetalum paraguayense (N. E. Br.) Walth. 1938, a perennial succulent plant in the Graptopetalum genus of the Crassulaceae family, is commonly known as Ghost Plant or Mother of Pearl. Native to arid regions such as Mexico, G. paraguayense features thick, flat leaves that are slightly pointed at the top, with an overall lotus-like shape that makes it highly ornamental. The leaf color varies depending on sunlight and environmental conditions: it appears blue-gray in the shade and pink in the sun. In addition to its aesthetic appeal, G. paraguayense is also regarded as a functional food and is used for its antihypertensive and hepatoprotective properties. It has been reported to exhibit a range of other bioactive effects, including anticancer, antibacterial, antiasthma, skin-whitening, and anti-Alzheimer’s activities [ 1 ] . Moreover, G. paraguayense extract (GP extract) has been shown to inhibit liver cancer cell growth and significantly prolong the lifespan of C. elegans [ 2 ] . The Crassulaceae family comprises 34 genera and over 1,500 species, including Aeonium , and Sedum . The subfamily Crassulaceae is divided into three subfamilies: Crassuloideae , Kalanchoideae , and Sempervivoideae . Within Sempervivoideae , there are five clades: the Telephium , Sempervivu , Aeonium , Leucosedum , Acre clades [ 3 ] . The focus of this study is G. paraguayense , which belongs to the Graptopetalum genus of the Acre clade. Previous studies have utilized various molecular markers, such as nuclear ETS, internal transcribed spacer (ITS), and plastid DNA sequences (rpl16, trnL-F), to explore phylogenetic relationships within closely related genera, including Cyperus [ 4 ] . Mitochondria are semi-autonomous organelles found in most eukaryotic cells. Plant mitochondria typically range from 1 to 3 µm in length and about 0.5 µm in diameter, with each plant cell containing several hundred mitochondria [ 5 ] . The study of plant mitochondria began in earnest around the 1950s, following the first successful isolations of mitochondria from animal and plant tissues [ 6 ] . Plant mitogenomes are characterized by high rearrangement, low mutation rates, and large size [ 7 ] . The structural features of plant mitochondrial genomes are complex and can include various conformations such as Y-type, H-type, single-ring, linear, and multi-ring structures. The mitochondria of G. paraguayense in this study are of a ring-type configuration, with the size and form of the mitochondrial genome varying across plant species [ 8 ] . The structure and function of mitochondria are intricately linke [ 9 ] , and the mitochondrial genomes of different species exhibit considerable variability, with frequent recombination and horizontal gene transfer [ 10 ] . Plant mitochondrial are key organelles responsible for important cellular processes such as metabolism, respiration, and energy conversion [ 11 ] . Mitochondria play a key role in essential cellular processes such as metabolism, respiration, and energy conversion, and are often referred to as the "powerhouses" of the cell. As such, mitochondrial genomes are invaluable tools for studying eukaryotic evolution, genetic diversity, species identification, and new cultivar breeding. The mitochondrial DNA structure can also be used to trace common ancestry among different species [ 12 ] . Hengwu Ding et al. sequenced the mitogenome of Sedum plumbizincicola (Crassulaceae) using high-throughput sequencing technologies, combining long reads (Oxford Nanopore Technology) and short reads (Illumina). The mitogenome of S. plumbizincicola is 212,159 bp in size, with a GC content of 44.5%. It includes 31 protein-coding genes (PCGs), 14 tRNAs, 3 rRNAs, 2 ORFs, and 11 pseudogenes. Notably, there are 508 RNA editing sites, with 496 codon changes, most of which are nonsynonymous conversions. This RNA editing significantly mitigates the impact of DNA mutations. Phylogenetic analysis showed that S. plumbizincicola is closely related to Sedum album within the Crassulaceae family [ 7 ] . Similarly, Xiaolei Yu et al. sequenced the organelle genomes of three Rhodiola species ( R. wallichiana , R. crenulata , and R. sacra ) from the Qinghai-Tibet Plateau and compared their mitogenomes. The study revealed that although these species exhibited structural diversity, their mitogenomes showed slower rates of sequence evolution, with R. wallichiana and R. sacra being more closely related than R. crenulata [ 13 ] . While significant progress has been made in studying the mitogenomes of Crassulaceae plants, there remains a lack of research, especially concerning G. paraguayense . Given the ecological significance of Crassulaceae plants, understanding the mitogenomes of these species is crucial for elucidating their classification, phylogenetic relationships, and unique genetic phenomena. Furthermore, such studies could offer new insights into the evolutionary dynamics of Crassulaceae mitogenomes, which may also benefit future plant mitogenome research and breeding programs. In this study, we utilized Real-Time DNA Sequencing of Single Polymerase Molecules to sequence the full mitochondrial genome of G. paraguayense . The mitochondrial genome was then assembled and annotated, followed by sequence collinearity analysis and the construction of a mitochondrial genome map for G. paraguayense . We also performed codon usage bias analysis, repeat sequence identification, and Ka/Ks ratio analysis of the mitogenome. Additionally, we conducted phylogenetic tree analysis and examined chloroplast, nuclear, and mitochondrial homologous sequences. The mitochondrial genome data of G. paraguayense obtained in this study will help improve our understanding of the species' evolutionary relationships and provide valuable insights for its classification. 2. Materials and methods 2.1. Plant samples and mitochondrial genome sequencing Fresh leaves of Graptopetalum paraguayense were collected from the Nanjing Ligan Flower Base, Nanjing, Jiangsu Province, China (32°12′N, 119°10′E). Pick the succulent leaves that are growing well, fresh and undamaged. Healthy, undamaged succulent leaves were carefully selected, thoroughly washed with sterile water, and stored at -80℃. We commissioned Nanjing Genepioneer Biotechnologies (Nanjing, China) use Real-Time DNA Sequence from Single Polymerase Molecules. After quality assessment of the DNA samples, the DNA was fragmented and repair of DNA damage, end repair, adapter ligation, enzymatic digestion, and purification. Sequencing was performed on the PacBio Sequel II platform in HiFi mode. Then use the perl script to count the third-generation sequencing data. HiFi raw reads were assembled using PMAT2 software (v2.0.2, parameter: –g 5G). Assembly results were visualized and manually adjusted using Bandage (v0.8.1). HiFi reads were subsequently aligned to the assembled sequence using minimap2, and sequence polishing was performed with NextPolish to generate the final mitogenome assembly and adjust the corresponding GFA file. Protein-coding genes (PCGs) and ribosomal RNA (rRNA) genes were first aligned against published plant mitochondrial reference sequences using BLAST (v2.13.0), and the annotations were then manually refined based on information from closely related species. Transfer RNA (tRNAs) genes were annotated using tRNAscanSE ( http://lowelab.ucsc.edu/tRNAscan-SE/ ) [ 14 ] . Open reading frames (ORFs) were annotated by OpenReading Frame Finder ( http://www.ncbi.nlm.nih.gov/gorf/gorf.html ) with a minimum length of 102 bp, excluding redundant sequences or those overlapping known genes. Sequences>300bp were annotated by comparison with the nr database. RNA editing sites were predicted using PmtREP ( http://112.86.217.82:9919/#/tool/ alltool/detail/336) [ 15 ] , and final annotations were verified and manually curated. Finally. The circular mitochondrial genome map was drawn using OGDRAW ( https://chlorobox.mpimp-golm.mpg.de/OGDraw.html ). 2.2. Relative synonymous codon usage (RSCU) analyses Due to the principle of codon degeneracy, there are great differences in the usage of genome codons among different species, and the inequality of synonymous codon usage is called relative synonymous codon usage (RSCU), which is usually considered to be the comprehensive result of natural selection, species mutation and genetic drift. We use the perl script of Nanjing Genepioneer Biotechnologies (Nanjing,China) filter uniq CDS and calculate it. The calculation method of codon preference is: (the number of one codon encoding an amino acid / the number of all codons encoding the amino acid) / (1 / the type of codon encoding the amino acid), that is, (the actual use frequency of the codon / the theoretical use frequency of the codon). If RSCU > 1, it indicates that the codon is widely used. If RSCU < 1, it indicates that the codon is not often used. If RSCU = 1, it indicates that the codon is not biased in use. 2.3. Repeat sequences analysis Repeat sequences included simple sequence repeats (SSR), tandem and dispersed. SSR was identified by misa software (v1.0, parameter: 1–10 2–5 3–4 4 − 3 5 − 3 6 − 3) [ 16 ] , and tandem was identified by trf software ( trf409.linux64, parameter: 27 7 80 10 50 2000-f-d-m) [ 17 ] . Dispersed was identified using blastn (v2.10.1, parameters: -word _ size 7, evalue 1e-5, remove redundancy, remove tandem duplication) software and visualized using circos v0.69-5 [ 18 ] . 2.4. Ka/Ks analyses The ratio of Ka to Ks indicates the selection effect. Ka/Ks>1 indicating a positive selection effect, Ka/Ks>1 indicating a negative selection effect. We grouped the species selected for advanced analysis in pairs and extracted homologous gene pairs. These homologous gene pairs were then aligned using MAFFT v7.427 ( https://mafft.cbrc.jp/alignment/software/ ) [ 19 ] . After alignment, KaKs_Calculator v2.0 ( https://sourceforge.net/projects/kakscalculator2/ ) was used to calculate the Ka and Ks values of each gene pair, with the MLWL method selected for the calculations [ 20 ] . Finally, the ka/ks values of each pair of genes were counted and the box plot was drawn. 2.5. Mitogenome synteny analysis Using the nucmer (4.0.0beta2) software and the maxmatch parmeter, genomic alignment between other sequences and assembly sequences was performed to generate Dot-plot plots [ 21 ] . 2.6. Nucleotide Diversity and Phylogenetic Analysis The complete mitogenomes of 14 species (Table S1 ) were downloaded from GenBank ( https://www.ncbi.nlm.nih.gov/genbank/ ). Homologous gene sequences were globally aligned using MAFFT (v7.427, –auto mode), and nucleotide diversity (pi values) was calculated with DnaSP v [ 19 ] . For phylogenetic analysis, coding sequences (CDSs) were aligned with MAFFT and concatenated. The alignment was trimmed using trimAl (v1.4.rev15, parameter: –gt 0.7) [ 22 ] . The best-fit substitution model (GTR) was selected using jModelTest (v2.1.10). A maximum likelihood (ML) phylogenetic tree was then constructed using RAxML (v8.2.10, GTRGAMMA model, 1,000 bootstra) [ 23 ] . 2.7. Migration analyses of chloroplast-to-mitochondrial DNA Homologous sequences between chloroplast and mitochondrial genomes were identified using BLAST with an E-value threshold of 1e–5 and a minimum sequence identity of 70%. 3. Results 3.1. Mitochondrial gene organization and features The complete mitochondrial genome of Graptopetalum paraguayense has been deposited in NCBI under accession number PV256627. A circular map of the genome was generated using the OGDRAW platform (Fig. 1 ). The mitochondrial genome is 242,059 bp in length and has a GC content of 43.65%. A total of 50 genes were annotated, comprising 13 tRNA genes, 3 rRNA genes, 31 protein-coding (mRNA) genes, and 3 pseudogenes (Table 1 , TableS2). Detailed statistics are provided in Table S3. These results confirm that the assembled mitochondrial genome of G. paraguayense is of high quality. Table 1 The genes identified in the mitochondrial genome of G. paraguayense Group of genes Gene name ATP synthase atp 1 atp 4 atp 6 atp 8 atp 9 Cytohrome c biogenesis ccm B ccm C ccm Fc* ccm Fn* Ubiquinol cytochrome c reductase cob Cytochrome c oxidase cox 1 cox 2** cox 3 Maturases mat R Transport membrane protein mtt B NADH dehydrogenase nad 1**** nad 2**** nad 3 nad 4*** nad 4L nad 5**** nad 6 nad 7**** nad 9 Ribosomal proteins (LSU) rpl 10 rpl 16 rpl 5 Ribosomal proteins (SSU) # rps 3 # rps 4 rps 12 rps 13 rps 14 rps 7 Succinate dehydrogenase # sdh 4 Ribosomal RNAs rrn 18 rrn 26 rrn 5 Transfer RNAs trn E-TTC trn F-GAA(2) trn H-GTG trn M-CAT(6) trn Q-TTG trn W-CCA trn Y-GTA Notes: *: intron number; #Gene: Pseudo gene;Gene(2): Number of copies of multi-copy genes. RNA-editing sites in the mitochondrial genome were predicted based on multiple sequence alignment. The amino acid sequence of each target gene was compared with homologous sequences in the database, and changes at corresponding positions were recorded. Sites that fulfilled the criteria for RNA editing were considered potential RNA-editing sites [ 24 ] . We statistically analyzed the number of RNA edits for each gene (Fig. 2 ). After RNA editing, the hydrophilic and hydrophobic properties of the amino acids produced by codons may change (Fig. 2 , Table 2 ). Table 2 Effects of RNA editing on changes hydrophilicity and hydrophobicity of amino acid in the mitogenome of G. paraguayense . Type RNA-editing Number Percentage hydrophilic-hydrophilic CAC (H) = > TAC (Y) 8 CAT (H) = > TAT (Y) 17 CGC (R) = > TGC (C) 11 CGT (R) = > TGT (C) 27 total 63 10.52% hydrophilic-hydrophobic ACA (T) = > ATA (I) 6 ACC (T) = > ATC (I) 6 ACG (T) = > ATG (M) 9 ACT (T) = > ATT (I) 7 CGG (R) = > TGG (W) 36 TCA (S) = > TTA (L) 78 TCC (S) = > TTC (F) 34 TCG (S) = > TTG (L) 48 TCT (S) = > TTT (F) 60 total 284 47.41% CAG (Q) = > TAG (X) 1 total 2 0.33% hydrophobic-hydrophilic CCA(P) = > TCA(S) 8 CCC (P) = > TCC (S) 17 CCG (P) = > TCG (S) 5 CCT (P) = > TCT (S) 19 total 49 8.18% hydrophobic-hydrophobic CCA (P) = > CTA (L) 45 CCC (P) = > CTC (L) 15 CCC (P) = > TTC (F) 4 CCG (P) = > CTG (L) 35 CCT (P) = > CTT (L) 27 CCT (P) = > TTT (F) 14 CTC (L) = > TTC (F) 15 CTT (L) = > TTT (F) 22 GCA (A) = > GTA (V) 8 GCC (A) = > GTC (V) 4 GCG (A) = > GTG (V) 7 GCT (A) = > GTT (V) 5 total 201 33.56% All 599 100% 3.2. Codon use analysis of RSCU The mitochondrial genome of Graptopetalum paraguayense encodes 20 amino acids using the standard set of 64 codons. Our analysis showed that 30 codons have a RSCU value greater than 1, 32 codons have an RSCU value less than 1, and only one or two codons exhibit an RSCU value equal to 1, indicating no usage bias for those codons. These unbiased codons are AUG (Met) and UGG (Trp). Among stop codons, UAA has the highest RSCU value (1.9355), followed by GCU, which encodes alanine (Ala) with an RSCU of 1.6244. In contrast, the codon UAC, which encodes tyrosine (Tyr), shows the lowest RSCU value (0.438), suggesting it is rarely used (Fig. 3 , Table S4). Further analysis of specific amino acids revealed similar patterns of preferential codon usage. Among the four codons encoding Ala, GCU is used most frequently (RSCU = 1.6244). For arginine (Arg), CGA shows the highest usage among its six synonymous codons (RSCU = 1.3297). Among the four codons encoding glycine (Gly), GGA is the most frequent (RSCU = 1.4961). For leucine (Leu), UUA is the most preferred codon among the six options (RSCU = 1.5226). Similarly, for serine (Ser), UCU exhibits the highest usage frequency (RSCU = 1.28) (Fig. 3 , Table S4). 3.3. Analysis of repeat structures in the Graptopetalum.paraguayense mitochondrial genomes The repeat structures identified in the mitochondrial genome of G. paraguayense comprise three types: simple sequence repeats (SSRs), tandem repeats, and dispersed repeats. A total of 122 repeat elements were detected, including 59 SSRs, 1 tandem repeat, and 62 dispersed repeats (Fig. 4 , TableS5-S8). The circular representation in Fig. 4 clearly illustrates the distribution and connections of these repeats across the mitogenome. 3.4. Ka/Ks analyses In order to analyze the substitution rate of the mitochondrial genome of the H ō yue plant, We calculated G. paraguayense with Tetragonia tetragonoides , Sedum plumbizincicola , Rhodiola crenulata , Mammillaria huitzilopochtli , Mesembryanthemum crystallinum , Nopalea cochenillifera and Rhodiola rosea , Ka/Ks of 30 common genes, a box plot was made. These genes include: atp 1、 atp 4、 atp 6、 atp 8、 atp 9、 ccm B、 ccm C、 ccm Fc、 ccm Fn、 cob 、 cox 1、 cox 2、 cox 3、 mat R、 mtt B、 nad 1、 nad 2、 nad 3、 nad 4、 nad 4L、 nad 5、 nad 6、 nad 7、 nad 9、 rpl 10、 rpl 16、 rpl 5、 rps 12、 rps 13、 rps 7. Among them, only the median ka/Ks values of ccm B and nad 7 genes were greater than 1, showing a positive selection effect. There are 28 genes including atp 1、 atp 4、 atp 6、 atp 8、 atp 9、 ccm C、 ccm Fc、 ccm Fn、 cob 、 cox 1、 cox 2、 cox 3、 mat R、 mtt B、 nad 1、 nad 2、 nad 3、 nad 4、 nad 4L、 nad 5、 nad 6、 nad 9、 rpl 10、 rpl 16、 rpl 5、 rps 12、 rps 13、 rps 7. The Ka/Ks values of rpl10, rpl16, rpl5, rps12, rps13 and rps7 are less than 1, showing a negative selection effect, indicating that they have a purification selection effect. No gene has a Ka/Ks value equal to 1( Fig. 5 , Table S9). 3.5. Mitogenome synteny analysis The genome sequence of Graptopetalum paraguayense was compared pairwise with those of seven other plants to assess mitochondrial genome collinearity. The dot-plot results demonstrate that G. paraguayense shares numerous homologous collinear fragments with Tetragonia tetragonoides , Sedum plumbizincicola , Rhodiola crenulata , Mammillaria huitzilopochtli , Mesembryanthemum crystallinum , Nopalea cochenillifera , and Rhodiola rosea . Among these comparisons, the homologous sequences between G. paraguayense and S. plumbizincicola are the longest and exhibit the highest similarity (57.28%). In contrast, the homologous sequences between G. paraguayense and M. crystallinum account for only 10.72% of the total mitochondrial genome, indicating relatively low collinearity (Fig. 6 , Table S10). 3.6. Nucleotide Diversity and Phylogenetic Analysis of G. paraguayense Analysis of nucleotide diversity (Pi) in the protein-coding genes (PCGs) of the G. paraguayense mitochondrial genome revealed marked heterogeneity among genes. The atp9 gene exhibited the highest Pi value (0.15809), indicating the greatest sequence variability and potential evolutionary significance, followed by atp8 (Pi = 0.08645) and rpl5 (Pi = 0.07741). These highly variable regions (Pi ≥ 0.05) may serve as potential molecular markers for future population-genetic or phylogenetic investigations (Fig. 7 , Table S11). Phylogenetic analysis further revealed that G. paraguayense clusters with Sedum plumbizincicola as a strongly supported sister taxon. Species of Rhodiola formed a well-supported monophyletic clade, although divergence was evident within the genus; for example, R. crenulata was more closely related to R. rosea . This topology provides robust phylogenetic evidence for the taxonomic placement of G. paraguayense within the Acre clade and reflects its relatively low mitochondrial sequence variation, as illustrated by the 57.28% collinearity observed with S. plumbizincicola . 3.7. Analysis of homologous sequence of chloroplast and mitochondria BLAST searches were performed to identify homologous sequences shared between the chloroplast and mitochondrial genomes of G. paraguayense . The highest sequence similarity score reached 9378. The homologous region spans positions 113,918 − 119,671 bp in the chloroplast genome and positions 152,894 − 147,275 bp in the mitochondrial genome. Within this chloroplast region, the homologous segment contains the genes psaC, ndhE, ndhG, ndhI, ndhA, and ndhH (Fig. 9 ). 4. Discussion G. paraguayense is a perennial succulent plant in the genus of the family Crassulaceae. It possesses significant ornamental value, medicinal properties, and is recognized as a functional food [ 1 ] . Mitochondria, essential organelles in living organisms, primarily facilitate energy production and are crucial for sustaining vital activities [ 25 ][ 26 ] . Composed of dual membranes (outer and inner), mitochondria contain their own DNA and ribosomes [ 27 ] . They play pivotal roles in calcium ion storage and apoptosis regulation [ 28 ] . For secondary quality control, 5,000 randomly selected reads were aligned against the NT database (blastn v2.13.0), revealing 37.92% unmatched to known species, while all matched species constituted ≤ 2.0% ( G. amethystinum highest at 2.00%). 4.1. Assembly and Evolutionary Conservation of the G. paraguayense Mitochondrial Genome Based on PacBi Revio and other platforms, this study successfully assembled the mitochondrial genome of G. paraguayense , ensuring high resolution and validating the reliability of the assembly results. The mitochondrial genome size of G. paraguayense is 242,209 bp, which falls within a medium size range. It is larger than Rhodiola juparensis (202,019 bp) and Rhodiola crenulata (194,106 bp), but smaller than Sesuvium portulacastrum (392,221 bp), Tetragonia tetragonoides (347,227 bp), Mesembryanthemum crystallinum (1,005,707 bp), Mammillaria huitzilopochtli (2,052,004 bp), Selenicereus monacanthus (2,290,019 bp), Nopalea cochenillifera (1,156,235 bp), Pereskia aculeata (515,187 bp), Hevea spruceana (935,732 bp), and Excoecaria agallocha (704,003 bp). Its size is similar to Sedum plumbizincicola (212,159 bp), Rhodiola tangutica (257,378 bp), and Rhodiola rosea (259,150 bp). Similar to most plant mitogenomes (e.g., Helianthus annuus and Sedum plumbizincicola ), the rps2 gene was undetected in the G. paraguayense mitochondrial genome [ 29 ] . Additionally, the absence of rps10 and rps11 genes was observed in S. plumbizincicola , R. juparensis , R. tangutica , R. rosea , and R. crenulata , suggesting potential early evolutionary loss of these genes. The G. paraguayense mitogenome encodes 13 tRNAs and 3 rRNAs, consistent with counts in related species: S. plumbizincicola (14 tRNAs, 3 rRNAs), R. juparensis (11 tRNAs, 3 rRNAs), and R. tangutica (15 tRNAs, 3 rRNAs). The overall GC content (43.65%) aligns with values in S. plumbizincicola (44.51%), R. juparensis (44.58%), R. tangutica (44.24%), R. rosea (44.88%), and R. crenulata (45.21%). Notably, the GC content of protein-coding regions (PCGs, 43.1%) was significantly lower than in tRNA-coding regions (50.42%) and rRNA-coding regions (51.56%). Collectively, these findings indicate conserved evolutionary features in the G. paraguayense mitogenome shared with related species. The pervasive loss of rps 2, rps 10, and rps 11 across crassulaceae plants, combined with stable tRNA/rRNA gene counts and uniform GC content, suggests strong selective constraints on mitogenome architecture, potentially linked to functional optimization. 4.2. Analysis of codon usage There is a significant codon usage bias in this genome. Of all 64 codons, 30 had an RSCU value greater than 1 (used more frequently than expected by chance) and 32 had an RSCU value less than 1 (used less frequently than expected). Only two codons, AUG-Met and UGG-Trp, had RSCU values equal to 1, indicating no preference for their use. Among them, the stop codon UAA showed the strongest bias (RSCU = 1.9355), while the tyrosine codon UAC showed the weakest bias (RSCU = 0.438). Among the synonymous codons of multiple amino acids, alanine (Ala) preferred GCU (RSCU = 1.6244), arginine (Arg) preferred CGA (RSCU = 1.3297), and glycine (Gly) preferred GGA (RSCU = 1.4961). Leucine (Leu) preferred UUA (RSCU = 1.5226), and serine (Ser) preferred UCU (RSCU = 1.28). These preference patterns reflect the combined effects of natural selection, mutation pressure, and other factors on the mitochondrial genome during evolution [ 30 ] . In the mitochondrial genome of G. paraguayense , there were 30 codons with RSCU values greater than 1, of which 12 ended with A base and 16 ended with U base, indicating that the third base of the codon of G. paraguayense was preferred to use A/U. 4.3. Analysis of repetitive sequences in the mitochondrial genome of G. paraguayense and Ka/Ks ratio assessment This study identified 122 repeat sequences in the G. paraguayense mitochondrial genome, including 59 simple repeats, 1 tandem repeat, and 62 dispersed repeats. The tandem repeat has a length of 39 bp, spanning from position 89779 to 89855, as marked by the red short line in Fig. 4 . The shortest dispersed repeat is 30 bp in length, while the longest dispersed repeat measures 3472 bp. Their detailed locations are provided in the supplementary materials (Table S5-S8). To assess mitochondrial genome substitution rates in G. paraguayense , we calculated Ka/Ks ratios for 30 shared protein-coding genes across seven comparative species (G. paraguayense , T. tetragonoides , S. plumbizincicola , R. crenulata , M. huitzilopochtli , M. crystallinum , N. cochenillifera , R. rosea ) (Table S9). Boxplot analysis revealed that only ccm B and nad 7 exhibited median Ka/Ks > 1, indicating positive selection (Fig. 5 ). It is speculated that the ccm B and nad 7 genes may be key signals of G. paraguayense fast-adaptive evolutionary genes. The remaining 28 genes showed Ka/Ks < 1, This indicates that these PCGs and the key functional genes possess a high degree of conservation (Fig. 5 ) [ 31 ] . 4.4. Phylogenetic and Pi analysis Based on the nucleotide diversity (Pi) analysis, this study identified several highly variable genes (Pi ≥ 0.05) in the mitochondrial genome, including atp 9 (Pi = 0.15809), atp 8 (Pi = 0.08645), rpl 5 (Pi = 0.07741), cox 2 (Pi = 0.0662), ccm Fn (Pi = 0.06365), rps 7 (Pi = 0.06349), ccm C (Pi = 0.05701), ccm Fc (Pi = 0.05425), mtt B (Pi = 0.0534), nad 6 (Pi = 0.05369), and rps 13 (Pi = 0.05299). These genes not only exhibit significant nucleotide diversity but are also associated with a high number of variant sites (e.g., 66 sites in atp 9 and up to 194 sites in ccm Fn), indicating faster evolutionary rates and rich genetic polymorphism [ 32 ] . Therefore, they could serve as potential molecular markers for subsequent phylogenetic analyses of closely related species, investigations into population genetic structures, and studies of adaptive evolution. This provides critical insights into understanding the genetic diversity and evolutionary history of G. paraguayense [ 33 ] . Phylogenetic analysis strongly supported G. paraguayense and S. plumbizincicola as sister taxa, confirming G. paraguayense 's placement within the Acre clade. Rhodiola formed a monophyletic clade, albeit with internal divergence, such as the close relationship between R. crenulata and R. rosea . 5. Conclusions This study successfully assembled and annotated the complete mitochondrial genome of G. paraguayense for the first time. The genome measures 242,059 base pairs with a GC content of 43.65 percent, containing 50 functional genes including 31 protein-coding genes, 13 tRNA genes, 3 rRNA genes along with 3 pseudogenes. Analysis identified 599 RNA editing sites in the mitochondrial genome, with nearly half converting hydrophilic amino acids to hydrophobic forms, indicating RNA editing likely plays a significant role in regulating protein function [ 34 ] . Codon usage analysis revealed preferential use of GCU for alanine, CGA for arginine and UUA for leucine, while the stop codon UAA showed the strongest bias with an RSCU value of 1.9355. The genome contained 122 repetitive sequences, predominantly 62 dispersed repeats that may contribute substantially to structural variation. Evolutionary analysis detected positive selection acting on ccm B and nad 7 genes, suggesting their importance in adaptive evolution [ 35 ] . Comparative genomic analysis demonstrated closest similarity with Sedum plumbizincicola at 57.28 percent sequence identity, supporting their phylogenetic relationship. These eleven highly variable regions ( atp 9, atp 8, rpl 5, cox 2, ccm Fn, rps 7, ccm C, ccm Fc, mtt B, nad 6, and rps 13) can serve as potential molecular markers in population genetics. The study also found evidence of chloroplast gene transfer to mitochondria involving psa C and ndh genes, providing new evidence of inter-organellar DNA exchange. Phylogenetic reconstruction confirmed G. paraguayense and Sedum plumbizincicola as sister species within the Acre clade of Crassulaceae, while Rhodiola species formed a distinct monophyletic group. In summary, this pioneering work characterizes the mitochondrial genome architecture and evolutionary patterns of G. paraguayense , advancing our understanding of Crassulaceae genomics. The findings establish a foundation for future investigations into plant organelle evolution, adaptive mechanisms and phylogenetic relationships. The study provides valuable genomic resources for further research on this economically and medicinally important succulent species. Declarations Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This work was supported by the Natural Science Foundation from Jiangsu Province (No. BK20211128) and the project of innovative entrepreneurship training for college students in Jiangsu province (No. 202313843019Y, No. 202313843009Y and No. S202513843029). Author Contribution X Z: Data curation, Formal analysis, Funding acquisition, Investigation, Writing –original draft, Writing–review&editing. CQ L: Data curation, Formal analysis, Writing–original draft, Methodology. ZR L: Data curation, Writing–original draft, Methodology. L Z：Methodology. X D: supervised the project and revised the manuscript.All authors reviewed the manuscript. 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Supplementary Files SupplementaryTable.docx Cite Share Download PDF Status: Published Journal Publication published 03 Jan, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 24 Oct, 2025 Reviews received at journal 23 Oct, 2025 Reviews received at journal 18 Oct, 2025 Reviews received at journal 12 Oct, 2025 Reviewers agreed at journal 11 Oct, 2025 Reviewers agreed at journal 10 Oct, 2025 Reviewers agreed at journal 10 Oct, 2025 Reviewers invited by journal 03 Oct, 2025 Editor assigned by journal 03 Oct, 2025 Editor invited by journal 26 Sep, 2025 Submission checks completed at journal 25 Sep, 2025 First submitted to journal 25 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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2","display":"","copyAsset":false,"role":"figure","size":76908,"visible":true,"origin":"","legend":"\u003cp\u003eStatistics of the number of RNA editing sites for each gene.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7592618/v1/5b094a7bed03323da2d1cf7b.png"},{"id":93698835,"identity":"42e2d914-9abc-4983-be79-7f0be31ff907","added_by":"auto","created_at":"2025-10-16 15:08:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":119878,"visible":true,"origin":"","legend":"\u003cp\u003eRelative Synonymous Codon Usage (RSCU)Value bar chart. The upper part of the picture shows the total RSCU of the mitochondria of the \u003cem\u003eG.paraguayense\u003c/em\u003e, and the lower part represents the codons used.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7592618/v1/c3d5af014e5f1d4130583248.png"},{"id":93699349,"identity":"28693222-1a6e-49ce-aa54-554eeecc3d82","added_by":"auto","created_at":"2025-10-16 15:16:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":526914,"visible":true,"origin":"","legend":"\u003cp\u003eThe repeated sequence diagram in the mitogenomes of \u003cem\u003eG. paraguayense\u003c/em\u003e. The outermost circle represents the mitochondrial genome sequence, followed by simple repeat sequences, tandem repeat sequences, and scattered repeat sequences in sequence.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7592618/v1/e92f634664aa0f513a89919c.png"},{"id":93699352,"identity":"101f6b3a-8816-415a-8242-9b0ef87ab5c6","added_by":"auto","created_at":"2025-10-16 15:16:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":87208,"visible":true,"origin":"","legend":"\u003cp\u003eSpecies-based Ka/Ks bar line graph. The horizontal axis represents the gene name, and the vertical axis represents the ka/ks value. In the box plot, the upper and lower endpoints of the vertical lines above and below the rectangle respectively represent the upper and lower edges of the data, the thick line inside the rectangle represents the median, the upper and lower edges of the rectangle represent the upper and lower quartiles, and the dots outside the upper and lower edges of the data represent outliers.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7592618/v1/af65c396a65d667f8f575cac.png"},{"id":93698850,"identity":"e249e4f6-d768-43aa-9291-ae256bf9334f","added_by":"auto","created_at":"2025-10-16 15:08:50","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":122877,"visible":true,"origin":"","legend":"\u003cp\u003eCollinear analysis of mitochondrial sequences. The horizontal axis in each box represents the assembled sequence, and the vertical axis represents other sequences. The values in parentheses indicate the proportion of homologous sequences in the total genome. The red lines in the boxes represent forward alignments, and the blue lines represent reverse complementary alignments.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7592618/v1/bdef537934d4610637fa4106.png"},{"id":93699351,"identity":"1d415ea3-0904-4dc4-9054-4dfe01186350","added_by":"auto","created_at":"2025-10-16 15:16:50","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":71000,"visible":true,"origin":"","legend":"\u003cp\u003eGene Pi Value Line Chart. The x-axis represents gene names, and the y-axis indicates Pi values.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7592618/v1/e52c84da9346ed5dd76f87b0.png"},{"id":93698866,"identity":"3eeb050e-a776-4271-b335-3ae2c0a6d503","added_by":"auto","created_at":"2025-10-16 15:08:51","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":43543,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of mitochondrial system evolution. Evolutionary branch length: Also known as genetic variation or evolutionary distance. It represents the degree of change in evolutionary branches. The shorter it is, the smaller the difference and the closer the evolutionary distance. Distance scale: The unit length of the difference values between organisms or sequences, equivalent to the scale of an evolutionary tree. Bootstrap value: The bootstrap value is generally marked at the node position and is used to evaluate the credibility of the branch.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7592618/v1/77e0be86ac5834d840fd8bec.png"},{"id":93698858,"identity":"cbf9f68e-8a26-46d4-ad17-ad46e718aef3","added_by":"auto","created_at":"2025-10-16 15:08:50","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":494014,"visible":true,"origin":"","legend":"\u003cp\u003eHomologous sequences between chloroplast and mitochondrial genomes of \u003cem\u003eGraptopetalum paraguayense\u003c/em\u003e. Genes belonging to the same complex are represented by squares of the same color. Squares on the outer and inner rings indicate genes located on the forward and reverse strands, respectively. The connecting lines in the center represent homologous sequences\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7592618/v1/1b8cca0bd7f253394c078b81.png"},{"id":99545652,"identity":"6910129a-dd9f-41a6-b8fc-7d4c3efe0ec2","added_by":"auto","created_at":"2026-01-05 16:09:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2871166,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7592618/v1/ca6ab763-57e7-4500-92cc-b3849cac1f5f.pdf"},{"id":93698861,"identity":"ef7450eb-e9fe-4811-84a7-6ad6fd85a0f8","added_by":"auto","created_at":"2025-10-16 15:08:50","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":78670,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-7592618/v1/9c764d24330f579b8f5cc862.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative genomic and phylogenetic analyses of mitochondrial genomes of Graptopetalum paraguayense (N. E. Br.) Walth.1938","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e\u003cem\u003eGraptopetalum paraguayense (N. E. Br.)\u003c/em\u003e Walth. 1938, a perennial succulent plant in the \u003cem\u003eGraptopetalum\u003c/em\u003e genus of the \u003cem\u003eCrassulaceae\u003c/em\u003e family, is commonly known as Ghost Plant or Mother of Pearl. Native to arid regions such as Mexico, \u003cem\u003eG. paraguayense\u003c/em\u003e features thick, flat leaves that are slightly pointed at the top, with an overall lotus-like shape that makes it highly ornamental. The leaf color varies depending on sunlight and environmental conditions: it appears blue-gray in the shade and pink in the sun. In addition to its aesthetic appeal, \u003cem\u003eG. paraguayense\u003c/em\u003e is also regarded as a functional food and is used for its antihypertensive and hepatoprotective properties. It has been reported to exhibit a range of other bioactive effects, including anticancer, antibacterial, antiasthma, skin-whitening, and anti-Alzheimer\u0026rsquo;s activities\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Moreover, \u003cem\u003eG. paraguayense\u003c/em\u003e extract (GP extract) has been shown to inhibit liver cancer cell growth and significantly prolong the lifespan of \u003cem\u003eC. elegans\u003c/em\u003e\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe \u003cem\u003eCrassulaceae\u003c/em\u003e family comprises 34 genera and over 1,500 species, including \u003cem\u003eAeonium\u003c/em\u003e, and \u003cem\u003eSedum\u003c/em\u003e. The subfamily \u003cem\u003eCrassulaceae\u003c/em\u003e is divided into three subfamilies: \u003cem\u003eCrassuloideae\u003c/em\u003e, \u003cem\u003eKalanchoideae\u003c/em\u003e, and \u003cem\u003eSempervivoideae\u003c/em\u003e. Within \u003cem\u003eSempervivoideae\u003c/em\u003e, there are five clades: the \u003cem\u003eTelephium\u003c/em\u003e, \u003cem\u003eSempervivu\u003c/em\u003e, \u003cem\u003eAeonium\u003c/em\u003e, \u003cem\u003eLeucosedum\u003c/em\u003e, \u003cem\u003eAcre\u003c/em\u003e clades\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. The focus of this study is \u003cem\u003eG. paraguayense\u003c/em\u003e, which belongs to the \u003cem\u003eGraptopetalum\u003c/em\u003e genus of the \u003cem\u003eAcre\u003c/em\u003e clade. Previous studies have utilized various molecular markers, such as nuclear ETS, internal transcribed spacer (ITS), and plastid DNA sequences (rpl16, trnL-F), to explore phylogenetic relationships within closely related genera, including \u003cem\u003eCyperus\u003c/em\u003e\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eMitochondria are semi-autonomous organelles found in most eukaryotic cells. Plant mitochondria typically range from 1 to 3 \u0026micro;m in length and about 0.5 \u0026micro;m in diameter, with each plant cell containing several hundred mitochondria\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. The study of plant mitochondria began in earnest around the 1950s, following the first successful isolations of mitochondria from animal and plant tissues\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Plant mitogenomes are characterized by high rearrangement, low mutation rates, and large size\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. The structural features of plant mitochondrial genomes are complex and can include various conformations such as Y-type, H-type, single-ring, linear, and multi-ring structures. The mitochondria of \u003cem\u003eG. paraguayense\u003c/em\u003e in this study are of a ring-type configuration, with the size and form of the mitochondrial genome varying across plant species\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. The structure and function of mitochondria are intricately linke\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e, and the mitochondrial genomes of different species exhibit considerable variability, with frequent recombination and horizontal gene transfer\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Plant mitochondrial are key organelles responsible for important cellular processes such as metabolism, respiration, and energy conversion\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Mitochondria play a key role in essential cellular processes such as metabolism, respiration, and energy conversion, and are often referred to as the \"powerhouses\" of the cell. As such, mitochondrial genomes are invaluable tools for studying eukaryotic evolution, genetic diversity, species identification, and new cultivar breeding. The mitochondrial DNA structure can also be used to trace common ancestry among different species\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eHengwu Ding et al. sequenced the mitogenome of \u003cem\u003eSedum plumbizincicola\u003c/em\u003e (Crassulaceae) using high-throughput sequencing technologies, combining long reads (Oxford Nanopore Technology) and short reads (Illumina). The mitogenome of \u003cem\u003eS. plumbizincicola\u003c/em\u003e is 212,159 bp in size, with a GC content of 44.5%. It includes 31 protein-coding genes (PCGs), 14 tRNAs, 3 rRNAs, 2 ORFs, and 11 pseudogenes. Notably, there are 508 RNA editing sites, with 496 codon changes, most of which are nonsynonymous conversions. This RNA editing significantly mitigates the impact of DNA mutations. Phylogenetic analysis showed that \u003cem\u003eS. plumbizincicola\u003c/em\u003e is closely related to \u003cem\u003eSedum album\u003c/em\u003e within the \u003cem\u003eCrassulaceae\u003c/em\u003e family\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Similarly, Xiaolei Yu et al. sequenced the organelle genomes of three \u003cem\u003eRhodiola\u003c/em\u003e species (\u003cem\u003eR. wallichiana\u003c/em\u003e, \u003cem\u003eR. crenulata\u003c/em\u003e, and \u003cem\u003eR. sacra\u003c/em\u003e) from the Qinghai-Tibet Plateau and compared their mitogenomes. The study revealed that although these species exhibited structural diversity, their mitogenomes showed slower rates of sequence evolution, with \u003cem\u003eR. wallichiana\u003c/em\u003e and \u003cem\u003eR. sacra\u003c/em\u003e being more closely related than \u003cem\u003eR. crenulata\u003c/em\u003e\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWhile significant progress has been made in studying the mitogenomes of \u003cem\u003eCrassulaceae\u003c/em\u003e plants, there remains a lack of research, especially concerning \u003cem\u003eG. paraguayense\u003c/em\u003e. Given the ecological significance of \u003cem\u003eCrassulaceae\u003c/em\u003e plants, understanding the mitogenomes of these species is crucial for elucidating their classification, phylogenetic relationships, and unique genetic phenomena. Furthermore, such studies could offer new insights into the evolutionary dynamics of \u003cem\u003eCrassulaceae\u003c/em\u003e mitogenomes, which may also benefit future plant mitogenome research and breeding programs.\u003c/p\u003e\u003cp\u003eIn this study, we utilized Real-Time DNA Sequencing of Single Polymerase Molecules to sequence the full mitochondrial genome of \u003cem\u003eG. paraguayense\u003c/em\u003e. The mitochondrial genome was then assembled and annotated, followed by sequence collinearity analysis and the construction of a mitochondrial genome map for \u003cem\u003eG. paraguayense\u003c/em\u003e. We also performed codon usage bias analysis, repeat sequence identification, and Ka/Ks ratio analysis of the mitogenome. Additionally, we conducted phylogenetic tree analysis and examined chloroplast, nuclear, and mitochondrial homologous sequences. The mitochondrial genome data of \u003cem\u003eG. paraguayense\u003c/em\u003e obtained in this study will help improve our understanding of the species' evolutionary relationships and provide valuable insights for its classification.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Plant samples and mitochondrial genome sequencing\u003c/h2\u003e\u003cp\u003eFresh leaves of \u003cem\u003eGraptopetalum paraguayense\u003c/em\u003e were collected from the Nanjing Ligan Flower Base, Nanjing, Jiangsu Province, China (32\u0026deg;12\u0026prime;N, 119\u0026deg;10\u0026prime;E). Pick the succulent leaves that are growing well, fresh and undamaged. Healthy, undamaged succulent leaves were carefully selected, thoroughly washed with sterile water, and stored at -80℃. We commissioned Nanjing Genepioneer Biotechnologies (Nanjing, China) use Real-Time DNA Sequence from Single Polymerase Molecules. After quality assessment of the DNA samples, the DNA was fragmented and repair of DNA damage, end repair, adapter ligation, enzymatic digestion, and purification. Sequencing was performed on the PacBio Sequel II platform in HiFi mode. Then use the perl script to count the third-generation sequencing data.\u003c/p\u003e\u003cp\u003eHiFi raw reads were assembled using PMAT2 software (v2.0.2, parameter: \u0026ndash;g 5G). Assembly results were visualized and manually adjusted using Bandage (v0.8.1). HiFi reads were subsequently aligned to the assembled sequence using minimap2, and sequence polishing was performed with NextPolish to generate the final mitogenome assembly and adjust the corresponding GFA file.\u003c/p\u003e\u003cp\u003eProtein-coding genes (PCGs) and ribosomal RNA (rRNA) genes were first aligned against published plant mitochondrial reference sequences using BLAST (v2.13.0), and the annotations were then manually refined based on information from closely related species. Transfer RNA (tRNAs) genes were annotated using tRNAscanSE (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://lowelab.ucsc.edu/tRNAscan-SE/\u003c/span\u003e\u003cspan address=\"http://lowelab.ucsc.edu/tRNAscan-SE/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Open reading frames (ORFs) were annotated by OpenReading Frame Finder (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ncbi.nlm.nih.gov/gorf/gorf.html\u003c/span\u003e\u003cspan address=\"http://www.ncbi.nlm.nih.gov/gorf/gorf.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) with a minimum length of 102 bp, excluding redundant sequences or those overlapping known genes. Sequences\u0026gt;300bp were annotated by comparison with the nr database. RNA editing sites were predicted using PmtREP (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://112.86.217.82:9919/#/tool/\u003c/span\u003e\u003cspan address=\"http://112.86.217.82:9919/#/tool/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e alltool/detail/336)\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e, and final annotations were verified and manually curated. Finally. The circular mitochondrial genome map was drawn using OGDRAW (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://chlorobox.mpimp-golm.mpg.de/OGDraw.html\u003c/span\u003e\u003cspan address=\"https://chlorobox.mpimp-golm.mpg.de/OGDraw.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Relative synonymous codon usage (RSCU) analyses\u003c/h2\u003e\u003cp\u003eDue to the principle of codon degeneracy, there are great differences in the usage of genome codons among different species, and the inequality of synonymous codon usage is called relative synonymous codon usage (RSCU), which is usually considered to be the comprehensive result of natural selection, species mutation and genetic drift. We use the perl script of Nanjing Genepioneer Biotechnologies (Nanjing,China) filter uniq CDS and calculate it. The calculation method of codon preference is: (the number of one codon encoding an amino acid / the number of all codons encoding the amino acid) / (1 / the type of codon encoding the amino acid), that is, (the actual use frequency of the codon / the theoretical use frequency of the codon). If RSCU\u0026thinsp;\u0026gt;\u0026thinsp;1, it indicates that the codon is widely used. If RSCU\u0026thinsp;\u0026lt;\u0026thinsp;1, it indicates that the codon is not often used. If RSCU\u0026thinsp;=\u0026thinsp;1, it indicates that the codon is not biased in use.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Repeat sequences analysis\u003c/h2\u003e\u003cp\u003eRepeat sequences included simple sequence repeats (SSR), tandem and dispersed. SSR was identified by misa software (v1.0, parameter: 1\u0026ndash;10 2\u0026ndash;5 3\u0026ndash;4 4\u0026thinsp;\u0026minus;\u0026thinsp;3 5\u0026thinsp;\u0026minus;\u0026thinsp;3 6\u0026thinsp;\u0026minus;\u0026thinsp;3)\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e, and tandem was identified by trf software ( trf409.linux64, parameter: 27 7 80 10 50 2000-f-d-m)\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Dispersed was identified using blastn (v2.10.1, parameters: -word _ size 7, evalue 1e-5, remove redundancy, remove tandem duplication) software and visualized using circos v0.69-5\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Ka/Ks analyses\u003c/h2\u003e\u003cp\u003eThe ratio of Ka to Ks indicates the selection effect. Ka/Ks\u0026gt;1 indicating a positive selection effect, Ka/Ks\u0026gt;1 indicating a negative selection effect. We grouped the species selected for advanced analysis in pairs and extracted homologous gene pairs. These homologous gene pairs were then aligned using MAFFT v7.427 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://mafft.cbrc.jp/alignment/software/\u003c/span\u003e\u003cspan address=\"https://mafft.cbrc.jp/alignment/software/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. After alignment, KaKs_Calculator v2.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://sourceforge.net/projects/kakscalculator2/\u003c/span\u003e\u003cspan address=\"https://sourceforge.net/projects/kakscalculator2/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to calculate the Ka and Ks values of each gene pair, with the MLWL method selected for the calculations\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Finally, the ka/ks values of each pair of genes were counted and the box plot was drawn.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Mitogenome synteny analysis\u003c/h2\u003e\u003cp\u003eUsing the nucmer (4.0.0beta2) software and the maxmatch parmeter, genomic alignment between other sequences and assembly sequences was performed to generate Dot-plot plots\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6. Nucleotide Diversity and Phylogenetic Analysis\u003c/h2\u003e\u003cp\u003eThe complete mitogenomes of 14 species (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) were downloaded from GenBank (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/genbank/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/genbank/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Homologous gene sequences were globally aligned using MAFFT (v7.427, \u0026ndash;auto mode), and nucleotide diversity (pi values) was calculated with DnaSP v\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFor phylogenetic analysis, coding sequences (CDSs) were aligned with MAFFT and concatenated. The alignment was trimmed using trimAl (v1.4.rev15, parameter: \u0026ndash;gt 0.7)\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. The best-fit substitution model (GTR) was selected using jModelTest (v2.1.10). A maximum likelihood (ML) phylogenetic tree was then constructed using RAxML (v8.2.10, GTRGAMMA model, 1,000 bootstra)\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.7. Migration analyses of chloroplast-to-mitochondrial DNA\u003c/h2\u003e\u003cp\u003eHomologous sequences between chloroplast and mitochondrial genomes were identified using BLAST with an E-value threshold of 1e\u0026ndash;5 and a minimum sequence identity of 70%.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Mitochondrial gene organization and features\u003c/h2\u003e\u003cp\u003eThe complete mitochondrial genome of \u003cem\u003eGraptopetalum paraguayense\u003c/em\u003e has been deposited in NCBI under accession number PV256627. A circular map of the genome was generated using the OGDRAW platform (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The mitochondrial genome is 242,059 bp in length and has a GC content of 43.65%. A total of 50 genes were annotated, comprising 13 tRNA genes, 3 rRNA genes, 31 protein-coding (mRNA) genes, and 3 pseudogenes (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, TableS2). Detailed statistics are provided in Table S3. These results confirm that the assembled mitochondrial genome of \u003cem\u003eG. paraguayense\u003c/em\u003e is of high quality.\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\u003eThe genes identified in the mitochondrial genome of \u003cem\u003eG. paraguayense\u003c/em\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\u003eGene name\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eATP synthase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eatp\u003c/em\u003e1 \u003cem\u003eatp\u003c/em\u003e4 \u003cem\u003eatp\u003c/em\u003e6 \u003cem\u003eatp\u003c/em\u003e8 \u003cem\u003eatp\u003c/em\u003e9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCytohrome c biogenesis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eccm\u003c/em\u003eB \u003cem\u003eccm\u003c/em\u003eC \u003cem\u003eccm\u003c/em\u003eFc* \u003cem\u003eccm\u003c/em\u003eFn*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUbiquinol cytochrome c reductase\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\u003eCytochrome c oxidase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ecox\u003c/em\u003e1 \u003cem\u003ecox\u003c/em\u003e2** \u003cem\u003ecox\u003c/em\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaturases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003emat\u003c/em\u003eR\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\u003emtt\u003c/em\u003eB\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNADH dehydrogenase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003enad\u003c/em\u003e1**** \u003cem\u003enad\u003c/em\u003e2**** \u003cem\u003enad\u003c/em\u003e3 \u003cem\u003enad\u003c/em\u003e4*** \u003cem\u003enad\u003c/em\u003e4L \u003cem\u003enad\u003c/em\u003e5**** \u003cem\u003enad\u003c/em\u003e6 \u003cem\u003enad\u003c/em\u003e7**** \u003cem\u003enad\u003c/em\u003e9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRibosomal proteins (LSU)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003erpl\u003c/em\u003e10 \u003cem\u003erpl\u003c/em\u003e16 \u003cem\u003erpl\u003c/em\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRibosomal proteins (SSU)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e#\u003cem\u003erps\u003c/em\u003e3 #\u003cem\u003erps\u003c/em\u003e4 \u003cem\u003erps\u003c/em\u003e12 \u003cem\u003erps\u003c/em\u003e13 \u003cem\u003erps\u003c/em\u003e14 \u003cem\u003erps\u003c/em\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSuccinate dehydrogenase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e#\u003cem\u003esdh\u003c/em\u003e4\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\u003errn\u003c/em\u003e18 \u003cem\u003errn\u003c/em\u003e26 \u003cem\u003errn\u003c/em\u003e5\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\u003etrn\u003c/em\u003eE-TTC \u003cem\u003etrn\u003c/em\u003eF-GAA(2) \u003cem\u003etrn\u003c/em\u003eH-GTG \u003cem\u003etrn\u003c/em\u003eM-CAT(6) \u003cem\u003etrn\u003c/em\u003eQ-TTG \u003cem\u003etrn\u003c/em\u003eW-CCA \u003cem\u003etrn\u003c/em\u003eY-GTA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003eNotes: *: intron number; #Gene: Pseudo gene;Gene(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\u003eRNA-editing sites in the mitochondrial genome were predicted based on multiple sequence alignment. The amino acid sequence of each target gene was compared with homologous sequences in the database, and changes at corresponding positions were recorded. Sites that fulfilled the criteria for RNA editing were considered potential RNA-editing sites\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. We statistically analyzed the number of RNA edits for each gene (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). After RNA editing, the hydrophilic and hydrophobic properties of the amino acids produced by codons may change (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\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\u003eEffects of RNA editing on changes hydrophilicity and hydrophobicity of amino acid in the mitogenome of \u003cem\u003eG. paraguayense\u003c/em\u003e.\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" 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\"\u003e\u003cp\u003ehydrophilic-hydrophilic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCAC (H)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TAC (Y)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eCAT (H)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TAT (Y)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eCGC (R)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TGC (C)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eCGT (R)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TGT (C)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003etotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.52%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ehydrophilic-hydrophobic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eACA (T)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;ATA (I)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eACC (T)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;ATC (I)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eACG (T)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;ATG (M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eACT (T)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;ATT (I)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eCGG (R)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TGG (W)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eTCA (S)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TTA (L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eTCC (S)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TTC (F)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eTCG (S)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TTG (L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eTCT (S)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TTT (F)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003etotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e284\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47.41%\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\u003eCAG (Q)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TAG (X)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003etotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.33%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ehydrophobic-hydrophilic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\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\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCCA(P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TCA(S)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eCCC (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TCC (S)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eCCG (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TCG (S)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eCCT (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TCT (S)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003etotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.18%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ehydrophobic-hydrophobic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCCA (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;CTA (L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eCCC (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;CTC (L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eCCC (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TTC (F)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eCCG (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;CTG (L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eCCT (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;CTT (L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eCCT (P)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TTT (F)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eCTC (L)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TTC (F)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eCTT (L)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;TTT (F)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eGCA (A)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;GTA (V)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eGCC (A)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;GTC (V)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eGCG (A)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;GTG (V)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003eGCT (A)\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;GTT (V)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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\u003etotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e201\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.56%\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\u003eAll\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e599\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100%\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=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Codon use analysis of RSCU\u003c/h2\u003e\u003cp\u003eThe mitochondrial genome of \u003cem\u003eGraptopetalum paraguayense\u003c/em\u003e encodes 20 amino acids using the standard set of 64 codons. Our analysis showed that 30 codons have a RSCU value greater than 1, 32 codons have an RSCU value less than 1, and only one or two codons exhibit an RSCU value equal to 1, indicating no usage bias for those codons. These unbiased codons are AUG (Met) and UGG (Trp). Among stop codons, UAA has the highest RSCU value (1.9355), followed by GCU, which encodes alanine (Ala) with an RSCU of 1.6244. In contrast, the codon UAC, which encodes tyrosine (Tyr), shows the lowest RSCU value (0.438), suggesting it is rarely used (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Table S4).\u003c/p\u003e\u003cp\u003eFurther analysis of specific amino acids revealed similar patterns of preferential codon usage. Among the four codons encoding Ala, GCU is used most frequently (RSCU\u0026thinsp;=\u0026thinsp;1.6244). For arginine (Arg), CGA shows the highest usage among its six synonymous codons (RSCU\u0026thinsp;=\u0026thinsp;1.3297). Among the four codons encoding glycine (Gly), GGA is the most frequent (RSCU\u0026thinsp;=\u0026thinsp;1.4961). For leucine (Leu), UUA is the most preferred codon among the six options (RSCU\u0026thinsp;=\u0026thinsp;1.5226). Similarly, for serine (Ser), UCU exhibits the highest usage frequency (RSCU\u0026thinsp;=\u0026thinsp;1.28) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Table S4).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Analysis of repeat structures in the \u003cem\u003eGraptopetalum.paraguayense\u003c/em\u003e mitochondrial genomes\u003c/h2\u003e\u003cp\u003eThe repeat structures identified in the mitochondrial genome of \u003cem\u003eG. paraguayense\u003c/em\u003e comprise three types: simple sequence repeats (SSRs), tandem repeats, and dispersed repeats. A total of 122 repeat elements were detected, including 59 SSRs, 1 tandem repeat, and 62 dispersed repeats (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, TableS5-S8). The circular representation in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e clearly illustrates the distribution and connections of these repeats across the mitogenome.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.4. Ka/Ks analyses\u003c/h2\u003e\u003cp\u003eIn order to analyze the substitution rate of the mitochondrial genome of the H ō yue plant, We calculated \u003cem\u003eG. paraguayense\u003c/em\u003e with \u003cem\u003eTetragonia tetragonoides\u003c/em\u003e, \u003cem\u003eSedum plumbizincicola\u003c/em\u003e, \u003cem\u003eRhodiola crenulata\u003c/em\u003e, \u003cem\u003eMammillaria huitzilopochtli\u003c/em\u003e, \u003cem\u003eMesembryanthemum crystallinum\u003c/em\u003e, \u003cem\u003eNopalea cochenillifera\u003c/em\u003e and \u003cem\u003eRhodiola rosea\u003c/em\u003e, Ka/Ks of 30 common genes, a box plot was made. These genes include: \u003cem\u003eatp\u003c/em\u003e1、\u003cem\u003eatp\u003c/em\u003e4、\u003cem\u003eatp\u003c/em\u003e6、\u003cem\u003eatp\u003c/em\u003e8、\u003cem\u003eatp\u003c/em\u003e9、\u003cem\u003eccm\u003c/em\u003eB、\u003cem\u003eccm\u003c/em\u003eC、\u003cem\u003eccm\u003c/em\u003eFc、\u003cem\u003eccm\u003c/em\u003eFn、\u003cem\u003ecob\u003c/em\u003e、\u003cem\u003ecox\u003c/em\u003e1、\u003cem\u003ecox\u003c/em\u003e2、\u003cem\u003ecox\u003c/em\u003e3、\u003cem\u003emat\u003c/em\u003eR、\u003cem\u003emtt\u003c/em\u003eB、\u003cem\u003enad\u003c/em\u003e1、\u003cem\u003enad\u003c/em\u003e2、\u003cem\u003enad\u003c/em\u003e3、\u003cem\u003enad\u003c/em\u003e4、\u003cem\u003enad\u003c/em\u003e4L、\u003cem\u003enad\u003c/em\u003e5、\u003cem\u003enad\u003c/em\u003e6、\u003cem\u003enad\u003c/em\u003e7、\u003cem\u003enad\u003c/em\u003e9、\u003cem\u003erpl\u003c/em\u003e10、\u003cem\u003erpl\u003c/em\u003e16、\u003cem\u003erpl\u003c/em\u003e5、\u003cem\u003erps\u003c/em\u003e12、\u003cem\u003erps\u003c/em\u003e13、\u003cem\u003erps\u003c/em\u003e7. Among them, only the median ka/Ks values of \u003cem\u003eccm\u003c/em\u003eB and \u003cem\u003enad\u003c/em\u003e7 genes were greater than 1, showing a positive selection effect. There are 28 genes including \u003cem\u003eatp\u003c/em\u003e1、\u003cem\u003eatp\u003c/em\u003e4、\u003cem\u003eatp\u003c/em\u003e6、\u003cem\u003eatp\u003c/em\u003e8、\u003cem\u003eatp\u003c/em\u003e9、\u003cem\u003eccm\u003c/em\u003eC、\u003cem\u003eccm\u003c/em\u003eFc、\u003cem\u003eccm\u003c/em\u003eFn、\u003cem\u003ecob\u003c/em\u003e、\u003cem\u003ecox\u003c/em\u003e1、\u003cem\u003ecox\u003c/em\u003e2、\u003cem\u003ecox\u003c/em\u003e3、\u003cem\u003emat\u003c/em\u003eR、\u003cem\u003emtt\u003c/em\u003eB、\u003cem\u003enad\u003c/em\u003e1、\u003cem\u003enad\u003c/em\u003e2、\u003cem\u003enad\u003c/em\u003e3、\u003cem\u003enad\u003c/em\u003e4、\u003cem\u003enad\u003c/em\u003e4L、\u003cem\u003enad\u003c/em\u003e5、\u003cem\u003enad\u003c/em\u003e6、\u003cem\u003enad\u003c/em\u003e9、\u003cem\u003erpl\u003c/em\u003e10、\u003cem\u003erpl\u003c/em\u003e16、\u003cem\u003erpl\u003c/em\u003e5、\u003cem\u003erps\u003c/em\u003e12、\u003cem\u003erps\u003c/em\u003e13、\u003cem\u003erps\u003c/em\u003e7. The Ka/Ks values of rpl10, rpl16, rpl5, rps12, rps13 and rps7 are less than 1, showing a negative selection effect, indicating that they have a purification selection effect. No gene has a Ka/Ks value equal to 1( Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Table S9).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.5. Mitogenome synteny analysis\u003c/h2\u003e\u003cp\u003eThe genome sequence of \u003cem\u003eGraptopetalum paraguayense\u003c/em\u003e was compared pairwise with those of seven other plants to assess mitochondrial genome collinearity. The dot-plot results demonstrate that \u003cem\u003eG. paraguayense\u003c/em\u003e shares numerous homologous collinear fragments with \u003cem\u003eTetragonia tetragonoides\u003c/em\u003e, \u003cem\u003eSedum plumbizincicola\u003c/em\u003e, \u003cem\u003eRhodiola crenulata\u003c/em\u003e, \u003cem\u003eMammillaria huitzilopochtli\u003c/em\u003e, \u003cem\u003eMesembryanthemum crystallinum\u003c/em\u003e, \u003cem\u003eNopalea cochenillifera\u003c/em\u003e, and \u003cem\u003eRhodiola rosea\u003c/em\u003e. Among these comparisons, the homologous sequences between \u003cem\u003eG. paraguayense\u003c/em\u003e and \u003cem\u003eS. plumbizincicola\u003c/em\u003e are the longest and exhibit the highest similarity (57.28%). In contrast, the homologous sequences between \u003cem\u003eG. paraguayense\u003c/em\u003e and \u003cem\u003eM. crystallinum\u003c/em\u003e account for only 10.72% of the total mitochondrial genome, indicating relatively low collinearity (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, Table S10).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.6. Nucleotide Diversity and Phylogenetic Analysis of \u003cem\u003eG. paraguayense\u003c/em\u003e\u003c/h2\u003e\u003cp\u003eAnalysis of nucleotide diversity (Pi) in the protein-coding genes (PCGs) of the \u003cem\u003eG. paraguayense\u003c/em\u003e mitochondrial genome revealed marked heterogeneity among genes. The \u003cem\u003eatp9\u003c/em\u003e gene exhibited the highest Pi value (0.15809), indicating the greatest sequence variability and potential evolutionary significance, followed by \u003cem\u003eatp8\u003c/em\u003e (Pi\u0026thinsp;=\u0026thinsp;0.08645) and \u003cem\u003erpl5\u003c/em\u003e (Pi\u0026thinsp;=\u0026thinsp;0.07741). These highly variable regions (Pi\u0026thinsp;\u0026ge;\u0026thinsp;0.05) may serve as potential molecular markers for future population-genetic or phylogenetic investigations (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, Table S11).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePhylogenetic analysis further revealed that \u003cem\u003eG. paraguayense\u003c/em\u003e clusters with \u003cem\u003eSedum plumbizincicola\u003c/em\u003e as a strongly supported sister taxon. Species of \u003cem\u003eRhodiola\u003c/em\u003e formed a well-supported monophyletic clade, although divergence was evident within the genus; for example, \u003cem\u003eR. crenulata\u003c/em\u003e was more closely related to \u003cem\u003eR. rosea\u003c/em\u003e. This topology provides robust phylogenetic evidence for the taxonomic placement of \u003cem\u003eG. paraguayense\u003c/em\u003e within the Acre clade and reflects its relatively low mitochondrial sequence variation, as illustrated by the 57.28% collinearity observed with \u003cem\u003eS. plumbizincicola\u003c/em\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e3.7. Analysis of homologous sequence of chloroplast and mitochondria\u003c/h2\u003e\u003cp\u003eBLAST searches were performed to identify homologous sequences shared between the chloroplast and mitochondrial genomes of \u003cem\u003eG. paraguayense\u003c/em\u003e. The highest sequence similarity score reached 9378. The homologous region spans positions 113,918\u0026thinsp;\u0026minus;\u0026thinsp;119,671 bp in the chloroplast genome and positions 152,894\u0026thinsp;\u0026minus;\u0026thinsp;147,275 bp in the mitochondrial genome. Within this chloroplast region, the homologous segment contains the genes psaC, ndhE, ndhG, ndhI, ndhA, and ndhH (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e\u003cem\u003eG. paraguayense\u003c/em\u003e is a perennial succulent plant in the genus of the family Crassulaceae. It possesses significant ornamental value, medicinal properties, and is recognized as a functional food\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Mitochondria, essential organelles in living organisms, primarily facilitate energy production and are crucial for sustaining vital activities\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e][\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. Composed of dual membranes (outer and inner), mitochondria contain their own DNA and ribosomes\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. They play pivotal roles in calcium ion storage and apoptosis regulation\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. For secondary quality control, 5,000 randomly selected reads were aligned against the NT database (blastn v2.13.0), revealing 37.92% unmatched to known species, while all matched species constituted\u0026thinsp;\u0026le;\u0026thinsp;2.0% (\u003cem\u003eG. amethystinum\u003c/em\u003e highest at 2.00%).\u003c/p\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Assembly and Evolutionary Conservation of the \u003cem\u003eG. paraguayense\u003c/em\u003e Mitochondrial Genome\u003c/h2\u003e\u003cp\u003eBased on PacBi Revio and other platforms, this study successfully assembled the mitochondrial genome of \u003cem\u003eG. paraguayense\u003c/em\u003e, ensuring high resolution and validating the reliability of the assembly results. The mitochondrial genome size of \u003cem\u003eG. paraguayense\u003c/em\u003e is 242,209 bp, which falls within a medium size range. It is larger than \u003cem\u003eRhodiola juparensis\u003c/em\u003e (202,019 bp) and \u003cem\u003eRhodiola crenulata\u003c/em\u003e (194,106 bp), but smaller than \u003cem\u003eSesuvium portulacastrum\u003c/em\u003e (392,221 bp), \u003cem\u003eTetragonia tetragonoides\u003c/em\u003e (347,227 bp), \u003cem\u003eMesembryanthemum crystallinum\u003c/em\u003e (1,005,707 bp), \u003cem\u003eMammillaria huitzilopochtli\u003c/em\u003e (2,052,004 bp), \u003cem\u003eSelenicereus monacanthus\u003c/em\u003e (2,290,019 bp), \u003cem\u003eNopalea cochenillifera\u003c/em\u003e (1,156,235 bp), \u003cem\u003ePereskia aculeata\u003c/em\u003e (515,187 bp), \u003cem\u003eHevea spruceana\u003c/em\u003e (935,732 bp), and \u003cem\u003eExcoecaria agallocha\u003c/em\u003e (704,003 bp). Its size is similar to \u003cem\u003eSedum plumbizincicola\u003c/em\u003e (212,159 bp), \u003cem\u003eRhodiola tangutica\u003c/em\u003e (257,378 bp), and \u003cem\u003eRhodiola rosea\u003c/em\u003e (259,150 bp).\u003c/p\u003e\u003cp\u003eSimilar to most plant mitogenomes (e.g., \u003cem\u003eHelianthus annuus\u003c/em\u003e and \u003cem\u003eSedum plumbizincicola\u003c/em\u003e), the rps2 gene was undetected in the \u003cem\u003eG. paraguayense\u003c/em\u003e mitochondrial genome\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. Additionally, the absence of rps10 and rps11 genes was observed in \u003cem\u003eS. plumbizincicola\u003c/em\u003e, \u003cem\u003eR. juparensis\u003c/em\u003e, \u003cem\u003eR. tangutica\u003c/em\u003e, \u003cem\u003eR. rosea\u003c/em\u003e, and \u003cem\u003eR. crenulata\u003c/em\u003e, suggesting potential early evolutionary loss of these genes. The \u003cem\u003eG. paraguayense\u003c/em\u003e mitogenome encodes 13 tRNAs and 3 rRNAs, consistent with counts in related species: \u003cem\u003eS. plumbizincicola\u003c/em\u003e (14 tRNAs, 3 rRNAs), \u003cem\u003eR. juparensis\u003c/em\u003e (11 tRNAs, 3 rRNAs), and \u003cem\u003eR. tangutica\u003c/em\u003e (15 tRNAs, 3 rRNAs). The overall GC content (43.65%) aligns with values in \u003cem\u003eS. plumbizincicola\u003c/em\u003e (44.51%), \u003cem\u003eR. juparensis\u003c/em\u003e (44.58%), \u003cem\u003eR. tangutica\u003c/em\u003e (44.24%), \u003cem\u003eR. rosea\u003c/em\u003e (44.88%), and \u003cem\u003eR. crenulata\u003c/em\u003e (45.21%). Notably, the GC content of protein-coding regions (PCGs, 43.1%) was significantly lower than in tRNA-coding regions (50.42%) and rRNA-coding regions (51.56%). Collectively, these findings indicate conserved evolutionary features in the \u003cem\u003eG. paraguayense\u003c/em\u003e mitogenome shared with related species. The pervasive loss of \u003cem\u003erps\u003c/em\u003e2, \u003cem\u003erps\u003c/em\u003e10, and \u003cem\u003erps\u003c/em\u003e11 across crassulaceae plants, combined with stable tRNA/rRNA gene counts and uniform GC content, suggests strong selective constraints on mitogenome architecture, potentially linked to functional optimization.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Analysis of codon usage\u003c/h2\u003e\u003cp\u003eThere is a significant codon usage bias in this genome. Of all 64 codons, 30 had an RSCU value greater than 1 (used more frequently than expected by chance) and 32 had an RSCU value less than 1 (used less frequently than expected). Only two codons, AUG-Met and UGG-Trp, had RSCU values equal to 1, indicating no preference for their use. Among them, the stop codon UAA showed the strongest bias (RSCU\u0026thinsp;=\u0026thinsp;1.9355), while the tyrosine codon UAC showed the weakest bias (RSCU\u0026thinsp;=\u0026thinsp;0.438). Among the synonymous codons of multiple amino acids, alanine (Ala) preferred GCU (RSCU\u0026thinsp;=\u0026thinsp;1.6244), arginine (Arg) preferred CGA (RSCU\u0026thinsp;=\u0026thinsp;1.3297), and glycine (Gly) preferred GGA (RSCU\u0026thinsp;=\u0026thinsp;1.4961). Leucine (Leu) preferred UUA (RSCU\u0026thinsp;=\u0026thinsp;1.5226), and serine (Ser) preferred UCU (RSCU\u0026thinsp;=\u0026thinsp;1.28). These preference patterns reflect the combined effects of natural selection, mutation pressure, and other factors on the mitochondrial genome during evolution\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. In the mitochondrial genome of \u003cem\u003eG. paraguayense\u003c/em\u003e, there were 30 codons with RSCU values greater than 1, of which 12 ended with A base and 16 ended with U base, indicating that the third base of the codon of \u003cem\u003eG. paraguayense\u003c/em\u003e was preferred to use A/U.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Analysis of repetitive sequences in the mitochondrial genome of \u003cem\u003eG. paraguayense\u003c/em\u003e and Ka/Ks ratio assessment\u003c/h2\u003e\u003cp\u003eThis study identified 122 repeat sequences in the \u003cem\u003eG. paraguayense\u003c/em\u003e mitochondrial genome, including 59 simple repeats, 1 tandem repeat, and 62 dispersed repeats. The tandem repeat has a length of 39 bp, spanning from position 89779 to 89855, as marked by the red short line in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The shortest dispersed repeat is 30 bp in length, while the longest dispersed repeat measures 3472 bp. Their detailed locations are provided in the supplementary materials (Table S5-S8).\u003c/p\u003e\u003cp\u003eTo assess mitochondrial genome substitution rates in \u003cem\u003eG. paraguayense\u003c/em\u003e, we calculated Ka/Ks ratios for 30 shared protein-coding genes across seven comparative species \u003cem\u003e(G. paraguayense\u003c/em\u003e, \u003cem\u003eT. tetragonoides\u003c/em\u003e, \u003cem\u003eS. plumbizincicola\u003c/em\u003e, \u003cem\u003eR. crenulata\u003c/em\u003e, \u003cem\u003eM. huitzilopochtli\u003c/em\u003e, \u003cem\u003eM. crystallinum\u003c/em\u003e, \u003cem\u003eN. cochenillifera\u003c/em\u003e, \u003cem\u003eR. rosea\u003c/em\u003e) (Table S9). Boxplot analysis revealed that only \u003cem\u003eccm\u003c/em\u003eB and \u003cem\u003enad\u003c/em\u003e7 exhibited median Ka/Ks\u0026thinsp;\u0026gt;\u0026thinsp;1, indicating positive selection (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). It is speculated that the \u003cem\u003eccm\u003c/em\u003eB and \u003cem\u003enad\u003c/em\u003e7 genes may be key signals of \u003cem\u003eG. paraguayense\u003c/em\u003e fast-adaptive evolutionary genes. The remaining 28 genes showed Ka/Ks\u0026thinsp;\u0026lt;\u0026thinsp;1, This indicates that these PCGs and the key functional genes possess a high degree of conservation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003e4.4. Phylogenetic and Pi analysis\u003c/h2\u003e\u003cp\u003eBased on the nucleotide diversity (Pi) analysis, this study identified several highly variable genes (Pi\u0026thinsp;\u0026ge;\u0026thinsp;0.05) in the mitochondrial genome, including \u003cem\u003eatp\u003c/em\u003e9 (Pi\u0026thinsp;=\u0026thinsp;0.15809), \u003cem\u003eatp\u003c/em\u003e8 (Pi\u0026thinsp;=\u0026thinsp;0.08645), \u003cem\u003erpl\u003c/em\u003e5 (Pi\u0026thinsp;=\u0026thinsp;0.07741), \u003cem\u003ecox\u003c/em\u003e2 (Pi\u0026thinsp;=\u0026thinsp;0.0662), \u003cem\u003eccm\u003c/em\u003eFn (Pi\u0026thinsp;=\u0026thinsp;0.06365), \u003cem\u003erps\u003c/em\u003e7 (Pi\u0026thinsp;=\u0026thinsp;0.06349), \u003cem\u003eccm\u003c/em\u003eC (Pi\u0026thinsp;=\u0026thinsp;0.05701), \u003cem\u003eccm\u003c/em\u003eFc (Pi\u0026thinsp;=\u0026thinsp;0.05425), \u003cem\u003emtt\u003c/em\u003eB (Pi\u0026thinsp;=\u0026thinsp;0.0534), \u003cem\u003enad\u003c/em\u003e6 (Pi\u0026thinsp;=\u0026thinsp;0.05369), and \u003cem\u003erps\u003c/em\u003e13 (Pi\u0026thinsp;=\u0026thinsp;0.05299). These genes not only exhibit significant nucleotide diversity but are also associated with a high number of variant sites (e.g., 66 sites in \u003cem\u003eatp\u003c/em\u003e9 and up to 194 sites in \u003cem\u003eccm\u003c/em\u003eFn), indicating faster evolutionary rates and rich genetic polymorphism\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. Therefore, they could serve as potential molecular markers for subsequent phylogenetic analyses of closely related species, investigations into population genetic structures, and studies of adaptive evolution. This provides critical insights into understanding the genetic diversity and evolutionary history of \u003cem\u003eG. paraguayense\u003c/em\u003e\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003ePhylogenetic analysis strongly supported \u003cem\u003eG. paraguayense\u003c/em\u003e and \u003cem\u003eS. plumbizincicola\u003c/em\u003e as sister taxa, confirming \u003cem\u003eG. paraguayense\u003c/em\u003e's placement within the Acre clade. Rhodiola formed a monophyletic clade, albeit with internal divergence, such as the close relationship between \u003cem\u003eR. crenulata\u003c/em\u003e and \u003cem\u003eR. rosea\u003c/em\u003e.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThis study successfully assembled and annotated the complete mitochondrial genome of \u003cem\u003eG. paraguayense\u003c/em\u003e for the first time. The genome measures 242,059 base pairs with a GC content of 43.65 percent, containing 50 functional genes including 31 protein-coding genes, 13 tRNA genes, 3 rRNA genes along with 3 pseudogenes. Analysis identified 599 RNA editing sites in the mitochondrial genome, with nearly half converting hydrophilic amino acids to hydrophobic forms, indicating RNA editing likely plays a significant role in regulating protein function\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eCodon usage analysis revealed preferential use of GCU for alanine, CGA for arginine and UUA for leucine, while the stop codon UAA showed the strongest bias with an RSCU value of 1.9355. The genome contained 122 repetitive sequences, predominantly 62 dispersed repeats that may contribute substantially to structural variation. Evolutionary analysis detected positive selection acting on \u003cem\u003eccm\u003c/em\u003eB and \u003cem\u003enad\u003c/em\u003e7 genes, suggesting their importance in adaptive evolution\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. Comparative genomic analysis demonstrated closest similarity with \u003cem\u003eSedum plumbizincicola\u003c/em\u003e at 57.28 percent sequence identity, supporting their phylogenetic relationship. These eleven highly variable regions (\u003cem\u003eatp\u003c/em\u003e9, \u003cem\u003eatp\u003c/em\u003e8, \u003cem\u003erpl\u003c/em\u003e5, \u003cem\u003ecox\u003c/em\u003e2, \u003cem\u003eccm\u003c/em\u003eFn, \u003cem\u003erps\u003c/em\u003e7, \u003cem\u003eccm\u003c/em\u003eC, \u003cem\u003eccm\u003c/em\u003eFc, \u003cem\u003emtt\u003c/em\u003eB, \u003cem\u003enad\u003c/em\u003e6, and \u003cem\u003erps\u003c/em\u003e13) can serve as potential molecular markers in population genetics. The study also found evidence of chloroplast gene transfer to mitochondria involving \u003cem\u003epsa\u003c/em\u003eC and \u003cem\u003endh\u003c/em\u003e genes, providing new evidence of inter-organellar DNA exchange. Phylogenetic reconstruction confirmed \u003cem\u003eG. paraguayense\u003c/em\u003e and \u003cem\u003eSedum plumbizincicola\u003c/em\u003e as sister species within the Acre clade of Crassulaceae, while Rhodiola species formed a distinct monophyletic group. In summary, this pioneering work characterizes the mitochondrial genome architecture and evolutionary patterns of \u003cem\u003eG. paraguayense\u003c/em\u003e, advancing our understanding of Crassulaceae genomics. The findings establish a foundation for future investigations into plant organelle evolution, adaptive mechanisms and phylogenetic relationships. The study provides valuable genomic resources for further research on this economically and medicinally important succulent species.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eDeclaration of competing interest\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis work was supported by the Natural Science Foundation from Jiangsu Province (No. BK20211128) and the project of innovative entrepreneurship training for college students in Jiangsu province (No. 202313843019Y, No. 202313843009Y and No. S202513843029).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eX Z: Data curation, Formal analysis, Funding acquisition, Investigation, Writing \u0026ndash;original draft, Writing\u0026ndash;review\u0026amp;editing. CQ L: Data curation, Formal analysis, Writing\u0026ndash;original draft, Methodology. ZR L: Data curation, Writing\u0026ndash;original draft, Methodology. L Z：Methodology. X D: supervised the project and revised the manuscript.All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data is available at NCBI accession: PV256627.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eV. Jaiswal, H.-J. Lee, A Comprehensive Review on Graptopetalum paraguayense\u0026rsquo;s Phytochemical Profiles, Pharmacological Activities, and Development as a Functional Food, 14(3) (2025) 349.\u003c/li\u003e\n \u003cli\u003eY.-X. Chen, P.T.N. Le, T.-T. Tzeng, T.-H. Tran, A.T. Nguyen, I.H.-J. Cheng, C.-Y.F. Huang, Y.-J. Shiao, T.-T. Ching, Graptopetalum paraguayense Extract Ameliorates Proteotoxicity in Aging and Age-Related Diseases in Model Systems, 13(12) (2021) 4317.\u003c/li\u003e\n \u003cli\u003eT.F.E. 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Bonnard, Wheat mitochondria ccmB encodes the membrane domain of a putative ABC transporter involved in cytochrome c biogenesis, Biochimica et Biophysica Acta (BBA) - Gene Structure and Expression 1519(3) (2001) 199-208.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Graptopetalum paraguayense, Mitochondrial genome, Phylogeny","lastPublishedDoi":"10.21203/rs.3.rs-7592618/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7592618/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eGraptopetalum paraguayense\u003c/em\u003e is a perennial succulent plant with ornamental value, functional value and medicinal activity. This study presents the first complete mitochondrial genome of \u003cem\u003eG. paraguayense\u003c/em\u003e. We assembled and annotated the complete mitochondrial genome of \u003cem\u003eG. paraguayense\u003c/em\u003e. we characterized a 242,059bp circular mitogenome with 43.65% GC content, harboring 50 functional genes (31 PCGs, 13 tRNAs, 3 rRNAs) and 3 pseudogenes. Identification of 599 RNA editing sites, predominantly altering amino acid hydrophobicity (47.41% hydrophilic-to-hydrophobic conversions). Codon usage bias analysis revealing preferential use of GCU (Ala), CGA (Arg), and UUA (Leu), with UAA stop codon exhibiting highest RSCU (1.9355). A total of 122 repetitive sequences were identified, including 59 Simple sequence repeat, 1 tandem repeat, and 62 dispersed repeat. Ka/Ks analysis indicating positive selection on \u003cem\u003eccm\u003c/em\u003eB and \u003cem\u003enad\u003c/em\u003e7 genes. \u003cem\u003eG. paraguayense\u003c/em\u003e shared 57.28% sequence similarity with Sedum plumbizincicola. Evidence of chloroplast-to-mitochondrial DNA transfer involving \u003cem\u003epsa\u003c/em\u003eC, \u003cem\u003endh\u003c/em\u003eE, \u003cem\u003endh\u003c/em\u003eG, \u003cem\u003endh\u003c/em\u003eI, \u003cem\u003endh\u003c/em\u003eA, \u003cem\u003endh\u003c/em\u003eH genes. Eleven divergent hotspot regions were identified by comparative analyses, were \u003cem\u003eatp9\u003c/em\u003e, \u003cem\u003eatp\u003c/em\u003e8, \u003cem\u003erpl\u003c/em\u003e5, \u003cem\u003ecox\u003c/em\u003e2, \u003cem\u003eccm\u003c/em\u003eFn, \u003cem\u003erps\u003c/em\u003e7, \u003cem\u003eccm\u003c/em\u003eC, \u003cem\u003eccm\u003c/em\u003eFc, \u003cem\u003emtt\u003c/em\u003eB, \u003cem\u003enad\u003c/em\u003e6 and \u003cem\u003erps\u003c/em\u003e13. Based on phylogenetic tree analysis, \u003cem\u003eG. paraguayense\u003c/em\u003e is highly related to \u003cem\u003eSedum plumbizincicola.\u003c/em\u003e These results provide foundational insights into mitogenome evolution in Crassulaceae, highlighting adaptive genetic mechanisms and interorganellar gene transfer in succulent plants.\u003c/p\u003e","manuscriptTitle":"Comparative genomic and phylogenetic analyses of mitochondrial genomes of Graptopetalum paraguayense (N. E. Br.) Walth.1938","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-16 15:08:37","doi":"10.21203/rs.3.rs-7592618/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-24T17:49:33+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-23T11:42:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-18T06:29:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-12T04:02:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"206624378899030353794188122989560120903","date":"2025-10-11T05:11:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"56029614926064248022521670494311148654","date":"2025-10-10T21:04:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"125362733724695895967908218581225035563","date":"2025-10-10T13:39:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-03T11:10:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-03T10:56:12+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-26T12:44:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-25T11:53:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-09-25T11:41:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0cd8182b-5fee-40e9-82be-e43dd83d3a30","owner":[],"postedDate":"October 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":56268068,"name":"Biological sciences/Biotechnology"},{"id":56268069,"name":"Biological sciences/Genetics"},{"id":56268070,"name":"Biological sciences/Molecular biology"},{"id":56268071,"name":"Biological sciences/Plant sciences"}],"tags":[],"updatedAt":"2026-01-05T16:07:47+00:00","versionOfRecord":{"articleIdentity":"rs-7592618","link":"https://doi.org/10.1038/s41598-025-34236-4","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-01-03 15:58:15","publishedOnDateReadable":"January 3rd, 2026"},"versionCreatedAt":"2025-10-16 15:08:37","video":"","vorDoi":"10.1038/s41598-025-34236-4","vorDoiUrl":"https://doi.org/10.1038/s41598-025-34236-4","workflowStages":[]},"version":"v1","identity":"rs-7592618","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7592618","identity":"rs-7592618","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}