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. 2025 Jul 1;26:602. doi: 10.1186/s12864-025-11817-1

Assembly and comparative analysis of the complete mitochondrial genome of Cardiocrinum giganteum: a primitive Liliaceae group with significant scientific research value

Zhiheng Zhao 1,#, Liyun Huang 1,#, Xiaolu Huang 1, Jianming Liao 1, Guangyu Zeng 1, Dan Liu 2,✉
PMCID: PMC12211521  PMID: 40597596

Abstract

Background 

Cardiocrinum giganteum, belonging to genus Cardiocrinum of family Liliaceae, is a genus endemic to East Asia and is considered one of the more primitive groups within the Liliaceae family. C. giganteum is the largest one among all the lily species in plant and flower size, and possesses high ornamental, medicinal, and scientific research value. However, due to its long-term wild status, its value has not been fully exploited and utilized, especially regarding the mitochondrial genome, which is crucial for plant growth activities, there have been no relevant studies and reports so far.

Results

In this study, we sequenced and assembled the complete mitochondrial genome of C. giganteum and elucidated its evolutionary trajectory and phylogenetic relationships. The C. giganteum mitogenome has a multi-chromosomal structure containing 19 circular molecules. The assembled mitogenome has a total length of 2,066,679 bp and a GC content of 44.54%. A total of 37 unique protein-coding genes (PCGs), 16 tRNA, and three rRNA genes were annotated. Several repetitive sequences and sequence fragments homologous to chloroplasts have also been found in the C. giganteum mitogenome. To determine the evolutionary and taxonomic positions of C. giganteum, we constructed a phylogenetic tree using C. giganteum mitochondrial PCGs. Additionally, we analyzed the relatively synonymous codon usage of PCGs, identified RNA editing events, and conducted syntenic analysis with closely related species.

Conclusions

This study presents the first comprehensive mitochondrial genome (mtDNA) characterization of C. giganteum (Liliaceae), revealing its unique multi-chromosomal configuration. Our findings address the knowledge gap in mitochondrial research within the Cardiocrinum genus while enriching the mitochondrial genome database of Liliaceae. The assembled mtDNA provides critical insights into the phylogenetic relationships between Cardiocrinum and its allied genera, establishing essential genomic resources for evolutionary analyses, species identification, and genetic diversity studies across Liliaceae.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-025-11817-1.

Keywords: Liliaceae, Cardiocrinum giganteum, Mitochondrial genome, Phylogenetic analysis

Introduction

Cardiocrinum giganteum belongs to the genus Cardiocrinum, within the family Liliaceae. It is a genus endemic to East Asia [1], the genus Cardiocrinum comprises only three species and one variety [2]. It is considered a sister group to the genus Fritillaria and is a sister group of the genus Lilium, occupying a relatively basal position in evolution, and is regarded as one of the more primitive groups within the Liliaceae family [3]. Moreover, the morphological characteristics and ecological habits of the genus Cardiocrinum also exhibit certain primitiveness. For instance, the plants are tall, being the largest in size among all lilies, with unique flower shapes. The flowers are large and elegant, and they mostly grow in moist areas such as under mountain forests [1]. The bulbs of C. giganteum are edible, and the fruits can be used in traditional medicine. It has high ornamental, medicinal, and scientific research values [4]. Due to its long-term wild status, the species’ potential value has not been fully exploited or utilized. Notably, research on its mitochondrial genome - which plays vital roles in plant growth and physiological activities - remains completely unreported to date.

The mitochondrial genome evolves relatively slowly, making it particularly suitable for tracing ancient evolutionary branches and exploring in-depth evolutionary relationships [5]. Since mitochondria play a crucial role in organisms and have a significant impact, the analysis and study of the mitochondrial genome have not only become a tool for researching species genetic markers but also a hot topic in fields such as evolutionary biology, genomics, and bioinformatics [6]. Since the mitochondrial genome of the first terrestrial plant, Marchantia polymorpha L.was sequenced in 1992 [7], the mitochondrial genomes of various higher plants have been studied, such as Beta vulgaris L [8]., Brassica napus L [9]., Nicotiana tabacum L [10]., Zea mays L [11]., and Oryza sativa L [12]., among others. The structure of the plant mitochondrial genome is complex, rich in repetitive sequences [13]. However, the number of basic functional genes does not change significantly, usually ranging between 50 and 60, and the complexity of the genome is relatively conserved [14]. Most plant mitochondrial genomes are considered to have a circular structure, for example, Actinidia macrosperma [15]. However, there are also other structures. For instance, Oryza sativa subsp [16] has a linear structure, Stemona tuberosa Lour [17] and Populus deltoides [18] have a multi-circular structure, and Picea sitchensis [19] has a multi-branched structure. Due to the replication and recombination of non-coding sequences, the sizes of mitochondrial genomes vary among different species [20, 21]. The mitochondrial genomes of some plants also contain many introns, which undergo trans-splicing after transcription [22]. The plant mitochondrial genome also exhibits a widespread phenomenon of RNA editing and uses some universal genetic codons [23, 24]. There are also many differences in the genetic patterns and sizes of mitochondrial genomes among different families, genera, and species of plants [25]. Therefore, studying the mitochondrial genome of C. giganteum not only helps in deeply understanding the genetic characteristics of C. giganteum and its phylogenetic relationships with several closely related families and genera but also fills the gap in the sequencing and analysis of the mitochondrial genomes of plants in the genus Cardiocrinum, providing a new perspective and data support for the phylogenetic study of Liliaceae plants.

However, current research on the Liliaceae family mainly focuses on aspects such as the identification of germplasm resources, determination of phylogenetic relationships, introduction and cultivation, and innovative propagation techniques [26–30]. The analysis of genomes mainly focuses on nuclear genomes and chloroplast genomes [27]. Due to the larger size, more complex structure, and greater difficulty in assembly of mitochondrial genomes, the sequencing speed of mitochondrial genomes is much lower than that of chloroplast genomes [31]. Among the plants of the genus Lilium, the number of published nuclear genomes and chloroplast genomes far exceeds that of mitochondrial genomes. For example, Yu et al. [32] published high-quality genome maps of Lilium sargentiae and Gloriosa superba in 2025. Wu et al. [33] published the chloroplast genomes of Lilium amoenum, Lilium souliei, and Nomocharis forrestii in 2022. As for the mitochondrial genome data of the genus Lilium, there are only those of Lilium pumilum and Lilium davidii published by Qi et al. [34] in 2020 and Lilium tsingtauense published by Qu et al. in 2024 [35]. In the genus Cardiocrinum, the chloroplast genomes of C. giganteum, C. cathayanum and C. cordatum have been sequenced [2], but none of the mitochondrial genomes have been sequenced yet. To understand the mitochondrial genome of C. giganteum and enrich the database of mitochondrial genomes of the Liliaceae family, we sequenced, assembled, and annotated the mitochondrial genome of C. giganteum, and analyzed its own sequence characteristics and the differences between it and the mitochondrial genomes of closely related species. These analyses include the GC content of the genome, codon usage bias, analysis of different types of repetitive sequences, phylogenetic analysis, analysis of RNA editing sites, and sequence migration analysis. The results of this study contribute to understanding the biological characteristics and phylogenetic status of this species, enriching the mitochondrial data of the genus Cardiocrinum, understanding the phylogenetic relationships between the genus Cardiocrinum and several other closely related species, and providing important data references for the genetic improvement, cultivation of new varieties, and molecular breeding of Liliaceae plants.

Materials and methods

Plant materials, DNA extraction, and sequencing

Plant Materials: The materials are fresh young leaves of the C. giganteum, collected from the C. giganteum base in Jianxin Village, Jiangdi Township, Longsheng Each Autonomous County, Guangxi (East Longitude 110°24′, North Latitude 25°83′). They are currently stored in the Chinese Plant Theme Database with the herbarium code KUN, barcode number 338,063, and the formal identifier is Shaoqing Chen. The tender leaf samples were quickly frozen in liquid nitrogen and stored at −80 °C. High-quality genomic DNA was extracted using the Tiangen DNA Extraction Kit (TIANamp Genoic DNA Kit).

Sequencing Methods: We sequenced and constructed the library of the C. giganteum mitochondrial genome using the Nanopore GridION (Oxford Nanopore Technology, Oxford Science Park) and Illumina NovaSeq 6000, and obtained Nanopore raw data 35.19 Gb and Illumina raw data 25.11 Gb. The detailed library preparation protocol was as follows:

  1. Select the corresponding testing methods for quality inspection according to the requirements of samples and products.

  2. Take the desired amount of animal RNA samples. The reaction system is configured. RNase H kit is used to remove rRNA.

  3. The reaction system is configured. After reacting at the suitable temperature for a fixed period of time, RNAs are fragmented.

  4. Add the preprepared first-strand synthesis reaction mixture into the fragmented RNAs. The reaction program is set up for synthesizing first-strand cDNAs. The reaction system and program are configured and set up for second-strand cDNA synthesis, dUTP instead of deoxythymidine triphosphate (dTTP) is used.

  5. After the reaction system and program are configured and setup, double-stranded cDNA fragments are subjected to end-repair, and then a single ‘A’ nucleotide is added to the 3’ ends of the blunt fragments. The reaction system and program for adaptor ligation are subsequently configured and setup to ligate adaptors with the cDNAs.

  6. The PCR reaction system and program are configured and setup to amplify the cDNAs.

  7. The corresponding library quality control protocol will be selected depending upon product requirements.

  8. Single-stranded PCR products are produced via denaturation. The reaction system and program for circularization are subsequently configured and set up. Single-stranded cyclized products are produced, while uncyclized linear DNA molecules are digested.

  9. Single-stranded circle DNA molecules are replicated via rolling cycle amplification, and a DNA nanoball (DNB) which contain multiple copies of DNA is generated. Sufficient quality DNBs are then loaded into patterned nanoarrays using high-intensity DNA nanochip technique and sequenced through combinatorial Probe-Anchor Synthesis (cPAS).

Genome assembly and annotation of the mitogenome

The conformations of plant mitochondrial genomes are diverse, hence the assembled mitochondrial genome configurations between different species also take on various shapes. In this study, we combined the use of Illumina and Nanopore sequencing and library construction, and then assembled the long-reads sequencing data using the software Flye [36] with default parameters. To understand the repetitive regions in the graph-based genome obtained after assembly, we aligned the long reads with the repetitive sequences using Flye, determining whether the long reads span the repetitive regions, thereby deducing the most likely structure of the mitochondrial genome. For all the assembled contigs in fasta format, we used makeblastdb to create a database, and then identified the contig fragments containing the mitochondrial genome using the BLASTn program with conserved mitochondrial genes of Arabidopsis thaliana as the query sequence, with parameters"-evalue 1e-5 -outfmt 6 -max_hsps 10 -word_size 7 -task blastn-short”. The software Bandage (v0.8.1) [37] was used to visualize the GFA file, and the mitochondrial contigs were filtered according to the results of BLASTn, obtaining a draft of the C. giganteum mitogenome. Subsequently, the BWA software (v0.7.17) [38] was used to align the long-reads and short-reads data to the mitochondrial contigs, and the aligned mitochondrial reads were filtered, exported, and saved for subsequent hybrid assembly. Finally, based on the combining of the aforementioned short-reads and long-reads sequencing data, the mitochondrial genome of the C. giganteum was hybrid assembled using the default parameters of Unicycler [39], and the mitochondrial genome was visualized using the Bandage software (v0.8.1) [37].

As each gene boundary of Arabidopsis thaliana (NC_037304) has been studied extensively and Liriodendron tulipifera (NC_021152.1) has a complete range of variable genes, we selected these two species as reference genomes to study the protein-coding genes in C. giganteum mitochondrial genome, and used the software PMGA [40] for gene annotation of the mitochondrial genome. The tRNA and rRNA of the mitochondrial genome were annotated respectively by using the software tRNAscan-SE (version 2.0.11) [41] and BLASTN (version 2.13.0) [42].Each annotation error was manually corrected using the Apollo software (version 1.11.8) [43].The chloroplast genome of C. giganteum was assembled using Getorganelle [44], annotated using Chloroplot [45], and the annotation was checked using cpgview [46].

Analysis of RSCU and repeated sequences

The usage of genetic codons in the genomes of different species and organisms varies significantly, which is believed to be a preference formed through long-term evolutionary selection. Therefore, analyzing codon preference (Relative Synonymous Codon Usage, RSCU) has also become a part of genomic analysis.In this study, the protein-coding sequences of the genome were extracted using the Phylosuite software (v1.1.16) [47], and then the codon preference of the protein-coding genes of the mitochondrial genome was analyzed using the Mega software (v7.0) [48], with the calculation of RSCU values. We identified microsatellite repeat sequences using MISA (v2.1) [49], tandem repeat sequences using TRF (v4.09) [50], and dispersed repeat sequences using the REPuter web server [51]. The results are visualized using Excel (2021) software and the Circos package (v0.69-9) [52].

Homology analysis and RNA editing site prediction

During the evolution of mitochondria, some fragments of the chloroplast genome migrate to the mitochondrial genome, and these migrated fragments vary in length and base sequence among different species. To analyze the migration of chloroplast genes to the mitochondrial genome in C. giganteum, we assembled and annotated the chloroplast genome of C. giganteum using the GetOrganelle software (v1.7.7.0) [44] and the Chloroplot software [45], respectively. Then, the annotation results were corrected using the CPGView software [46]. Finally, homologous fragments were analyzed using the BLASTN software (v2.13.0) [42], and the results were visualized using the Circos package (v0.69-9 [52].

Based on the data information obtained from transcriptome sequencing, the transcripts of the mitochondrial genome are filtered out and mapped to the mitochondrial DNA sequence. The BEDTools software (v2.30.0) [53] is used to further analyze and compare the sequence differences between DNA and RNA, in order to identify RNA editing events supported by the majority of reads. Used REDO tools on BAM files obtained from transcriptome read mapping, and RNA editing sites were identified based on REDO’s default filtering criteria, including minimum coverage and editing frequency thresholds.

Phylogenetic and syntenic analysis

Based on phylogenetic relationships, 19 species from five orders of angiosperms were selected.The best-fit model selected for the phylogenetic tree was GTR + F + I + R2, chosen according to the BIC. Based on phylogenetic relationships, 19 closely related species within the Liliaceae family were selected, and their mitochondrial genomes were retrieved from the National Center for Biotechnology Information (NCBI: https://www.ncbi.nlm.nih.gov), then the common mitochondrial genes were extracted by using software PhyloSuite [47]. We aligned the nucleotide sequences of the common genes using the MAFFT software (v7.505) [54], concatenated them to form a data matrix, and performed phylogenetic analysis based on the data matrix using the IQ-TREE software (v1.6.12) [55], with 1000 bootstrap replicates. Finally, we visualized the results of the phylogenetic analysis using the iTOL software (v6) [56].

The conserved homologous sequences identified by the BLASTn software were referred to as collinear blocks, with the parameters of'-evalue 1e-5, -word_size 9, -gapopen 5, -gapextend 2, -reward 2, -penalty − 3 ‘. Only collinear blocks longer than 500 bp were selected for further analysis. Based on the results obtained, the MCscanX [57] software was used to generate the pairwise comparison results of the Multiple Synteny Plot, thereby mapping out the conserved collinear blocks.

Results

Characteristics of the C. giganteum mitogenome

Using long-read sequencing data, we assembled a draft mitochondrial genome of C. giganteum (Fig. 1A) and visualized the assembly using Bandage (v0.8.1). The complete mitochondrial genome spans 2,066,679 base pairs (bp) with a GC content of 44.54%. The mitochondrial genome consists of 19 circular sequences (Fig. 1), with black lines on each circle indicating overlapping regions between sequences, suggesting a complex multichromosomal structure. Detailed information on sequence IDs, coverage depth, and lengths is provided in Table S1.

Fig. 1.

Fig. 1

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Characteristics of the C. giganteum mitogenome. A Assembly draft of the C. giganteum mitogenome. B Annotation results and genomic map of the C. giganteum mitogenome

In the mitochondrial genome of Cardiocrinum giganteum (Fig. 1B), we annotated 37 unique protein-coding genes, comprising 16 transfer RNA (tRNA) genes (including 7 multicopy tRNAs) and 3 ribosomal RNA (rRNA) genes. The core gene repertoire includes:5 ATP synthase genes: atp1, atp4, atp6, atp8, atp9; 9 NADH dehydrogenase genes: nad1, nad2, nad3, nad4, nad4L, nad5, nad6, nad7, nad9; 4 cytochrome c biogenesis genes: ccmB, ccmC, ccmFC, ccmFN; 3 cytochrome c oxidase genes: cox1, cox2, cox3; 1 membrane transporter gene: mttB; 1 maturase gene: matR and 1 ubiquinol-cytochrome c reductase gene: cob. The non-core complement contains: 2 large ribosomal subunit genes: rpl5, rpl16; 10 small ribosomal subunit genes: rps1, rps2, rps3, rps4, rps7, rps10, rps12, rps13, rps14, rps19 and 1 succinate dehydrogenase gene: sdh4. Complete gene inventory is presented in Table 1.

Table 1.

The MtDNA encoding genes of C. giganteum

Group of genes Name of genes
ATP synthase atp1, atp4, atp6, atp8, atp9 (×3)
NADH dehydrogenase nad1, nad2, nad3, nad4, nad4L, nad5, nad6, nad7, nad9
Cytochrome b cob
Cytochrome c biogenesis ccmB, ccmC, ccmFC, ccmFN
Cytochrome c oxidase cox1, cox2, cox3
Maturases matR
Protein transport subunit mttB (×2)
Ribosomal protein large subunit rpl5, rpl16 (×2)
Ribosomal protein small subunit rps1, rps2, rps3, rps4, rps7, rps10, rps12, rps13 (×2), rps14, rps19 (×2)
Succinate dehydrogenase sdh4
Ribosome RNA rrn5, rrn18, rrn26
Transfer RNA

trnC-GCA (×2), trnD-GUC (×3), trnE-UUC, trnF- GAA (×2), trnfM-CAU, trnH-GUG, trnI-CAU,

trnK-UUU, trnL-CAA (×2), trnM-CAU (×2),

trnN-GUU (×2), trnP-UGG, trnQ-UUG (×2),

trnT-UGU, trnW-CCA, trnY-GUA
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PCGs codon usage analysis

The codon preference patterns for each amino acid are detailed in Table S2. A relative synonymous codon usage (RSCU) value of 1 indicates no codon preference, while values > 1 represent preferred codons for a given amino acid. In the mitochondrial genome of C. giganteum, we identified 26 high-frequency codons (RSCU > 1), excluding the start codon AUG, tryptophan (UGG), and threonine (ACC), all of which showed RSCU values of 1.

Amino acid usage frequency analysis revealed that leucine (Leu), arginine (Arg), and serine (Ser) were the most frequently used, while methionine (Met) and tryptophan (Trp) exhibited the lowest frequencies (Fig. 2). Termination codons showed strong preference for UAA, which displayed the highest RSCU value (RSCU = 1.91) among all mitochondrial protein-coding genes. Alanine (Ala) preferentially utilized codon GCU (RSCU = 1.63). Notably, all NNA-type codons demonstrated RSCU values > 1.00, with only two exceptions: the alanine codon GCA (RSCU = 0.97) and the termination codon UGA (RSCU = 0.73) (Table S2).

Fig. 2.

Fig. 2

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Relative Synonymous Codon Usage (RSCU) in the C. giganteum mitogenome. The X-axis displays the codon families. The RSCU value represents the number of times the codon is observed relative to its usage in a uniform synonymous codon usage scenario

Repeat sequence analysis

The repetitive sequence analysis was conducted on 19 mitochondrial molecules. The results are depicted in Fig. 3.

Fig. 3.

Fig. 3

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Repeat sequence analysis of C. giganteum mitogenome. A Distribution of simple sequence repeats (SSRs) across mitochondrial molecules. The x-axis represents mitochondrial molecules, while the y-axis indicates the number of repeat units. Color-coded legend: monomeric SSRs (blue), dimeric SSRs (red), trimeric SSRs (gray), tetrameric SSRs (yellow), pentameric SSRs (purple), and hexameric SSRs (green). B Distribution of complex repeat types in mitochondrial molecules. The x-axis shows mitochondrial molecules, with the y-axis representing repeat unit counts. Legend: tandem repeats (green), palindromic repeats (orange), forward repeats (blue), reverse repeats (red), and complementary repeats (purple)

A total of 503 simple sequence repeats (SSRs) were identified across the 19 mitochondrial molecules of Cardiocrinum giganteum (Fig. 3A, Table S3). The SSR composition was as follows: 103 mononucleotide SSRs (20.48%), with adenine (A) repeats being most prevalent (58.25%); 126 dinucleotide SSRs (25.05%), dominated by AT repeats (26.19); 74 trinucleotide SSRs (14.71%), primarily AAG repeats (14.86%); 163 tetranucleotide SSRs (32.41%), with AAAG as the most frequent motif (8.59%); Pentanucleotide and hexanucleotide SSRs were less abundant, accounting for 6.36% and 1.19% of the total repeats, respectively.

A total of 40 tandem repeat sequences were detected in 19 molecules (Fig. 3B, Table S4). Tandem repeats were not detected in the 7th, 14th, 15th, and 19th molecules. The 12th, 16th, and 17th molecules each had only one tandem repeat detected, with match percentages of 88%, 100%, and 100% respectively. The 3rd, 4th, 6th, 9th, 11th, 13th, and 18th molecules each had two tandem repeats detected, with average match percentages of 94%, 88.5%, 85%, 82%, 81.5%, 93%, and 84.5% respectively. The 1 st molecule had three tandem repeats detected, with an average match percentage of 90%. The 2nd and 8th molecules each had four tandem repeats detected, with average match percentages of 87% and 96.3% respectively, and the 5th and 10th molecules both had six tandem repeats detected, with average match percentages of 88.8% and 90%.

In addition to SSR and tandem repeat sequences, we also discovered a large number of dispersed repetitive sequences in the mitochondrial genome of the C. giganteum (Fig. 3B, Table S5). A total of 478 pairs of repeat sequences with lengths greater than or equal to 30 were observed in 19 molecules of the C. giganteum mitogenome. Among these, the 1 st molecule had the highest number of detected repetitive sequences with 117 pairs. Within these repetitive sequences, including 67 pairs of palindromic sequences and 50 forward sequences. No complementary sequences were found in the 19 molecules, and only one reverse sequence was detected in the 10th molecule.

Homologous analysis of genome sequences

Through sequence similarity analysis, we identified 32 homologous fragments between the mitochondrial and chloroplast genomes, with a total length of 9,373 bp, accounting for 0.45% of the complete mitochondrial genome length (Fig. 4, Table S6). The most frequent sequence transfers occurred between the chloroplast genome and mitochondrial molecules M3、M4 、M5 and M11. The longest homologous fragment (1,119 bp) was located in molecule M26. Annotation of these 32 homologous fragments revealed four intact genes, all of which were transfer RNA (tRNA) genes: trnD-GUG, trnH-GUG, trnL-CAA, and trnW-CCA.

Fig. 4.

Fig. 4

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Homologous analysis of genome sequences. A C. giganteum chloroplast genome, B Schematic of gene transfer between the chloroplast and mitochondria of C. giganteum. Yellow arcs: mitochondrial genome. Green arcs: chloroplast genome. Purple connecting lines: homologous sequence regions

RNA editing site prediction

The predicted RNA editing sites in each gene are depicted in Fig. 5.

Fig. 5.

Fig. 5

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Distribution of RNA editing sites in the mitochondria genome of C. giganteum. The X-axis represents protein-coding genes and the Y-axis represents the number of RNA editing sites. Blue bars denote the number of RNA editing sites in C. giganteum, while black bars represent those in L.tsingtauense (for comparison)

As shown in Fig. 5, a total of 595 potential RNA editing sites were identified across the 37 mitochondrial protein-coding genes (PCGs) in C. giganteum, all of which were C-to-U edits(Table S7). The gene nad4 and ccmB had the highest number of RNA editing sites, with 51 identified. The gene rps7 and sdh5 had the fewest predicted editing sites, with only 2 each. In comparison, in the mitochondrial genome of L. tsingtauense, the ccmB gene had the most editing sites, with a total of 37, while the rps7 gene had the fewest editing sites, with only 2. Consistent numbers of editing sites were detected in the rps4, rps14, nad2, nad9, atp1, atp8, and atp9 genes between C. giganteum and L. tsingtauense(Fig. 5, Table S8).

Among the RNA editing sites, the type of 102 amino acids remained unchanged, 53.11% of the amino acids maintained their hydrophobicity, 37.31% of the amino acids changed from being hydrophilic to hydrophobic, and 8.91% of the amino acids changed from being hydrophobic to hydrophilic. In addition, RNA editing events introduced stop codons into atp6, atp9, ccmFC, and rps10 (Table S7).

Phylogenetic analysis

To determine the phylogenetic position of the C. giganteum, we constructed a phylogenetic tree for 19 species across five orders of angiosperms based on the sequences of 24 conserved mitochondrial protein-coding genes (PCGs) (atp1, atp4, atp6, atp8, atp9, ccmB, ccmC, ccmFC, ccmFN, cob, cox1, cox2, cox3, matR, mttB, nad1, nad2, nad3, nad4, nad4L, nad5, nad6, nad7, nad9). The mitochondrial genomes of the Aconitum kusnezoffii Rehder and Anemone maxima from the order Ranunculales were used as outgroups (Fig. 6). In the phylogenetic tree, out of the 16 nodes, 12 nodes had bootstrap support values greater than 90%, and 10 nodes had a bootstrap support value of 100%. Based on the topology of the mitochondrial DNA phylogeny, which coincides with the latest classification of the Angiosperm Phylogeny Group (APG), C. giganteum was assigned to the family Liliaceae in the order Liliales and clustered in one branch with the species of the genus Lilium.

Fig. 6.

Fig. 6

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Phylogenetic tree of 19 angiosperm species based on the sequences of 24 conserved mitochondrial PCGs. The numbers on each node represent the bootstrap support values. The blue area represents the order Asparagales; the yellow area, the order Liliales; the purple area, the order Arecales; the green area, the order Alismatales; and the pink area, the order Ranunculales (as an outgroup). C. giganteum is highlighted in bold red

Syntenic analysis

Based on sequence similarity, we used the source program MCscanX to plot multiple synteny plots of L. davidii and L. tsingtauense.(Fig. 7). The mitochondrial genome information of C. giganteum, L. davidii, and L. tsingtauense is presented in Table S8.

Fig. 7.

Fig. 7

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Homology of mitogenomes. The bar block representation indicates the mitochondrial genomes of different species, the red arc areas denote regions where inversions have occurred, and the gray areas signify regions with good homology. To better display the results, collinear blocks shorter than 0.5 kb in length have not been included in the presentation

Excluding collinear blocks of less than 0.5 kb in length, it was found that C. giganteum shares a large number of homologous collinear blocks with L. davidii and L. tsingtauense within the Liliaceae order. However, these collinear blocks were observed to be relatively short. (Fig. 7 and Table S9). The largest collinear block spanned approximately 52.8 kb and occurred between L. davidii and L. tsingtauense. The largest co-linear block spanning approximately 14.7 kb was found on the 4th ring chromosome of C. giganteum. This co-linear block occurred between C. giganteum and L. tsingtauense. The second largest co-linear block with a size of approximately 14.58 kb was found on the 5th ring chromosome, which also occurred between C. giganteum and L. tsingtauense. The smallest co-linear block spanning approximately 0.497 kb, occurred on the 9th ring chromosome of C. giganteum. Meanwhile, among the 19 chromosome s, the 1 st ring chromosome of the C. giganteum had the most number of co-lineage blocks, 28 in total, and the longest one was approximately 14.32 kb. The 18th ring chromosome had only one co-lineage block, which was 0.376 kb in length. In addition, some blank areas were discovered, indicating that these sequences are unique to the C. giganteum and do not share homology with the other species. The results demonstrate significant structural divergence in mitochondrial genome organization among the three Liliales species, with the mitochondrial genome of C. giganteum exhibiting extensive genomic rearrangements compared to its close relatives. This suggests remarkably low structural conservation in mitochondrial genome architecture within this lineage.

Discussion

Characteristics of the C. giganteum mitogenome

To date, no mitochondrial genome has been reported for any species in the genus Cardiocrinum. Within Liliaceae, the mitochondrial genome sizes of documented species show considerable variation: Fritillaria ussuriensis Maxim [58]. in the genus Fritillaria possesses a 737,569 bp mitochondrial genome, while in the genus Lilium, L. pumilum and L.davidii [34] exhibit mitochondrial genomes of 988,986 bp and 924,401 bp respectively. Notably, L.tsingtauense [35] demonstrates an expanded mitochondrial genome of 1,125,108 bp. In contrast, Allium cepa L.(onion) [59] from the genus Allium (Liliaceae) has a relatively compact mitochondrial genome of 324,182 bp. In this study, we successfully assembled the mitochondrial genome of C. giganteum, revealing an exceptional size of 2,066,679 bp - substantially larger than other reported Liliaceae mitochondrial genomes. We hypothesize that this expansion primarily results from abundant repetitive sequences, as evidenced by our detection of 503 SSRs in the C. giganteum mitochondrial genome, including 478 pairs ≥ 30 bp in length. This contrasts with the 221 SSRs (130 pairs ≥ 30 bp) reported in L. tsingtauense [35]. Our observation aligns with recent findings by Chen et al. [60], who demonstrated correlations between repetitive element abundance and mitochondrial genome size variation across Solanaceae species.

Although plant mitochondrial genome data remain limited, current evidence confirms diverse structural configurations beyond the canonical circular form, including linear and multichromosomal architectures [61]. Within Liliaceae, L. tsingtauense [35] maintains its mitochondrial genome as 27 distinct circular chromosomes, while F. ussuriensis [58] and Hemerocallis citrina [62] possess 13 and 3 circular chromosomes respectively. Our analysis of Nanopore data (excluding repetitive regions) reveals that C. giganteum primarily contains a multichromosomal mitochondrial genome comprising 19 circular sequences. However, the high recombination rates characteristic of plant mitochondrial genomes frequently generate subgenomic molecules through repeat-mediated rearrangements (inversions/deletions), which typically exist in dynamic equilibrium rather than as stable independent chromosomes [63]. While no subgenomic molecules were detected in our study, their potential presence cannot be entirely excluded. Furthermore, the stability of these structural configurations across different tissues or developmental stages remains unclear. Subsequent investigations will necessitate the implementation of more sensitive and advanced technical approaches, complemented by additional experiments, to enable comprehensive and precise detection.

Codon usage analysis of PCGs and repeat sequences

Eukaryotic genomes employ 64 codons to encode 20 amino acids and three termination signals. With the exception of methionine (AUG) and tryptophan (UGG), all amino acids are encoded by multiple synonymous codons. During evolution, organisms develop preferential codon usage patterns, a phenomenon attributed to cellular optimization processes [64]. For instance, L. tsingtauense exhibits a strong preference for the UAA termination codon [35]. In this study, we similarly observed predominant UAA usage as the termination codon in C. giganteum, demonstrating the highest Relative Synonymous Codon Usage (RSCU) value of 1.91 among mitochondrial protein-coding genes (PCGs). Research indicates that codon bias in developmental regulatory genes primarily manifests at the third nucleotide position of synonymous codons [65]. Our RSCU analysis revealed significant A/U enrichment at third codon positions in C. giganteum mitochondria, with NNA and NNU codons exhibiting RSCU values > 1. This AU-biased third-position preference aligns with observations in L. tsingtauense mitochondria [35].

Plant mitochondrial genomes harbor diverse repetitive elements, including SSRs, tandem repeats, and dispersed repeats, which play pivotal roles in mitochondrial evolution [66, 67]. Our analysis demonstrated overwhelming A/T dominance in mononucleotide SSRs, while dinucleotide SSRs showed the highest AT frequency (26.19%). Among trinucleotide SSRs, AAG repeats predominated (14.86%). The abundance of A/T-rich SSRs in C. giganteum directly contributes to its elevated mitochondrial A/T content, consistent with evolutionary trends in plant organellar genomes [68, 69]. Furthermore, we identified 40 tandem repeats and 478 repeat pairs ≥ 30 bp in length. These repetitive elements not only explain the exceptionally large mitochondrial genome size of C. giganteum compared to other Liliaceae species but also suggest frequent intermolecular recombination events [70, 71].

Homology analysis

Extensive genetic material exchange occurs between plant organelles in angiosperms, where chloroplast-derived sequences are transferred to mitochondria through mitochondrial-targeted plastid DNA (MTPT) events [72]. These transferred fragments typically constitute 1–12% of mitochondrial genome length [73]. For instance, chloroplast-mitochondrial homologous sequences account for 10.3% and 5.07% in Phoenix dactylifera L [74]. and Cocos nucifera [75]. (Arecaceae), respectively. Previous studies demonstrate substantial interspecific variation in both length and sequence composition of these homologous regions [76]. While foreign sequences have been identified in numerous plant mitochondrial genomes, they predominantly occur in non-coding regions or pseudogenes rather than functional coding sequences [77, 78]. Mitochondrial and chloroplast genomes of L.tsingtauense [35] share 18 homologous fragments totaling 2,848 bp, accounting for 0.25% of the mitochondrial genome length. The most frequent sequence transfers occurred between the chloroplast genome and regions M3, M10, and M11, with the longest homologous fragment measuring 620 bp. Annotation of these homologous sequences revealed two intact tRNA genes (trnH-GUG and trnW-CCA). In C. giganteum, we identified 32 homologous fragments between mitochondrial and chloroplast genomes, totaling 9,373 bp (0.45% of mitochondrial genome length). Multi-copy transfer hotspots were observed in M3, M4, M5, and M11 regions, with the longest homologous fragment spanning 1,119 bp. Annotation of these 32 fragments identified four intact tRNA genes (trnD-GUG, trnH-GUG, trnL-CAA, and trnW-CCA), including both genes found in L. tsingtauense. Comparative analysis suggests more conserved sequence transfer in C. giganteum, which exhibits greater numbers of homologous fragments and functional genes. This divergence may result from combined effects of growth environment, genomic architecture, and selection pressure. While we have identified these homologous sequences, their underlying mechanisms require further elucidation through integrated genomic studies, functional experiments, and phylogenetic analyses.

RNA editing sites prediction

RNA editing, a crucial post-transcriptional modification in higher plant mitochondria, plays essential roles in gene expression regulation. Investigation of RNA editing sites provides critical insights into organellar gene expression mechanisms and facilitates functional gene prediction [79, 80]. In plants, the predominant RNA editing type involves cytosine C-to-U conversions [81]. For instance, L.tsingtauense mitochondria exhibit 591 RNA editing sites exclusively displaying C-to-U modifications [35]. Our study identified 595 potential RNA editing sites in the C.giganteum mitochondrial genome, all demonstrating this conserved C-to-U editing pattern.

RNA editing exhibits a 92% probability of altering amino acid sequences, predominantly converting hydrophilic residues to hydrophobic ones, thereby facilitating proper protein folding and functionality [82]. In our study, among the 595 identified potential RNA editing sites, 37.31% resulted in such hydrophilic-to-hydrophobic amino acid conversions.Notably, RNA editing can generate novel start or stop codons, serving as a regulatory mechanism for gene expression. Premature stop codon formation through editing leads to truncated translation products that typically lack full biological functionality, consequently affecting both gene expression levels and protein function. Conversely, newly created start codons may activate translation of previously silent genomic regions, thereby expanding proteomic complexity [83].A representative example occurs in the mitochondrial genome of Hemerocallis citrina [62], where ACG-to-AUG editing introduces start codons in the nad1, nad4L, and rps10 genes, while CAA-to-UAA and CGA-to-UGA editing creates stop codons in atp6 and ccmFC. Similarly, our analysis revealed stop codon formation in the atp6, atp9, ccmFC, and rps10 genes of C.giganteum mitochondrial genome. Following these editing events, the encoded proteins demonstrated enhanced sequence conservation and higher homology with orthologous proteins from other species, suggesting improved mitochondrial gene expression efficiency [84].

Phylogenetic analysis and syntenic

With advancements in sequencing and assembly technologies, mitochondrial DNA has become increasingly valuable for phylogenetic analyses [85, 86]. Our mitochondrial phylogenomic reconstruction revealed that C. giganteum clusters with Lilium species (Liliaceae, Liliales) while maintaining distinct generic status, consistent with the latest Angiosperm Phylogeny Group (APG) classification. In 2020, Lu [2] conducted a chloroplast genome-wide sequencing analysis of Cardiocrinum, confirming its status as a monophyletic group and establishing a sister relationship between Cardiocrinum and the Lilium-Fritillaria clade. However, mitochondrial genomes exhibit extensive structural variation, abundant repetitive DNA, frequent gene loss, and nuclear transfers - all factors that may compromise phylogenetic accuracy [87]. Moreover, the uniparental inheritance and single-locus nature of chloroplast genomes [88, 89] might not fully resolve Cardiocrinum’s phylogenetic relationships. Therefore, nuclear genomic data will be essential for future verification of its systematic position.

Synteny analysis evaluates homologous gene/sequence arrangements to assess genome assembly quality and evolutionary patterns of gene retention/loss [90–93]. Our comparative analysis identified numerous short syntenic blocks (maximum span: 52.8 kb) between C. giganteum and related Liliales species, interspersed with species-specific sequences. This fragmented synteny pattern, coupled with extensive genomic rearrangements, demonstrates remarkable mitochondrial structural plasticity in C. giganteum. We propose that such dynamic genome architecture has been a major driver of mitochondrial evolution and diversification in this lineage.

Conclusions

This study presents the first report of the unique multi-chromosomal architecture in the mitochondrial genome of C. giganteum (19 circular contigs totaling 2,066,679 bp), addressing the knowledge gap in mitochondrial genome research within the Cardiocrinum genus and enriching the mitochondrial genome database of Liliaceae. The multi-chromosomal configuration of C. giganteum provides a model system for investigating mitochondrial structural diversification mechanisms in monocotyledons. Comprehensive analyses including codon preference, repetitive sequences, genome homology, RNA editing events, and phylogenetic relationships revealed that the C. giganteum mitochondrial genome contains substantially more repetitive sequences than related species, suggesting these elements may be the primary factor contributing to its exceptionally large genome size compared to other Liliaceae members. The identified chloroplast-to-mitochondrion gene transfer events further substantiate the ubiquitous nature of horizontal gene transfer between plant organellar genomes during evolution, providing critical insights into nuclear-organellar genome co-evolution. Although existing mitochondrial genome data within Liliaceae remains limited, the phylogenetic tree constructed with available species information robustly positions C. giganteum within the Liliaceae family, clustering specifically within the Lilium clade. These findings establish essential data resources for evolutionary studies, species identification, and genetic diversity research in Liliaceae plants.

Supplementary Information

Supplementary Material 1. (11.8KB, xlsx)
Supplementary Material 2. (12.8KB, xlsx)
Supplementary Material 3. (74.9KB, xlsx)
Supplementary Material 4. (12.9KB, xlsx)
Supplementary Material 5. (35.1KB, xlsx)
Supplementary Material 6. (13.8KB, xlsx)
Supplementary Material 7. (52.2KB, xlsx)
Supplementary Material 8. (11.9KB, xlsx)
Supplementary Material 9. (66.2KB, xlsx)

Acknowledgements

The authors acknowledge support from the laboratory and our collaborators for many useful suggestions. We sincerely thank the experimental personnel and bioinformatics analysts at Wuhan Benagen Tech Solutions Company Limited (www.benagen.com) and MitoRun research group participated in this project.

Data statement

The mitogenome sequences have been deposited in GenBank of NCBI (https://www.ncbi.nlm.nih.gov/) under the accession numbers PQ073105-PQ073123.

Authors’ contributions

Z.Z.: data analysis; writing—original draft preparation. H.L.: writing—original draft preparation; methodology. H.X.: resource investigation; methodology. L.J.: resource investigation. Z.G.: sample collection. L.D.: Conceptualization; writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This work was financially supported by the Guangxi Forestry science and technology promotion demonstration project（2023GXLK21；Guangxi Key Laboratory of Special Non-wood Forests Cultivation and Utilization Project（19-B-01-02.

Data availability

The mitogenome sequences have been deposited in GenBank of NCBI (https://www.ncbi.nlm.nih.gov/) under the accession numbers PQ073105-PQ073123.

Declarations

Ethical approval and consent to participate

This study’s material collections and experimental research complied with relevant institutional, national, and international guidelines and legislation. No specific permissions or licenses were required.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

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

Zhiheng Zhao and Liyun Huang contributed equally to this work.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1. (11.8KB, xlsx)
Supplementary Material 2. (12.8KB, xlsx)
Supplementary Material 3. (74.9KB, xlsx)
Supplementary Material 4. (12.9KB, xlsx)
Supplementary Material 5. (35.1KB, xlsx)
Supplementary Material 6. (13.8KB, xlsx)
Supplementary Material 7. (52.2KB, xlsx)
Supplementary Material 8. (11.9KB, xlsx)
Supplementary Material 9. (66.2KB, xlsx)

Data Availability Statement

The mitogenome sequences have been deposited in GenBank of NCBI (https://www.ncbi.nlm.nih.gov/) under the accession numbers PQ073105-PQ073123.

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