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Comparative analyses of three complete Primula mitogenomes with insights into mitogenome size variation in Ericales

Abstract

Background

Although knowledge of the sizes, contents, and forms of plant mitochondrial genomes (mitogenomes) is increasing, little is known about the mechanisms underlying their structural diversity. Evolutionary information on the mitogenomes of Primula, an important ornamental taxon, is more limited than the information on their nuclear and plastid counterparts, which has hindered the comprehensive understanding of Primula mitogenomic diversity and evolution. The present study reported and compared three Primula mitogenomes and discussed the size expansion of mitogenomes in Ericales.

Results

Mitogenome master circles were sequenced and successfully assembled for three Primula taxa and were compared with publicly available Ericales mitogenomes. The three mitogenomes contained similar gene contents and varied primarily in their structures. The Primula mitogenomes possessed relatively high nucleotide diversity among all examined plant lineages. In addition, high nucleotide diversity was found among Primula species between the Mediterranean and Himalaya-Hengduan Mountains. Most predicted RNA editing sites appeared in the second amino acid codon, increasing the hydrophobic character of the protein. An early stop in atp6 caused by RNA editing was conserved across all examined Ericales species. The interfamilial relationships within Ericales and interspecific relationships within Primula could be well resolved based on mitochondrial data. Transfer of the two longest mitochondrial plastid sequences (MTPTs) occurred before the divergence of Primula and its close relatives, and multiple independent transfers could also occur in a single MTPT sequence. Foreign sequence [MTPTs and mitochondrial nuclear DNA sequences (NUMTs)] uptake and repeats were to some extent associated with changes in Ericales mitogenome size, although none of these relationships were significant overall.

Conclusions

The present study revealed relatively conserved gene contents, gene clusters, RNA editing, and MTPTs but considerable structural variation in Primula mitogenomes. Relatively high nucleotide diversity was found in the Primula mitogenomes. In addition, mitogenomic genes, collinear gene clusters, and locally collinear blocks (LCBs) all showed phylogenetic signals. The evolutionary history of MTPTs in Primula was complicated, even in a single MTPT sequence. Various reasons for the size variation observed in Ericales mitogenomes were found.

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Background

The mitochondrion is one of three genetic compartments in plant cells that play a fundamental role in encoding several essential mitochondrial electron transfer chains [1, 2]. Only 321 plant mitochondrial genomes (mitogenomes) have been released in the NCBI organelle database (organelle genome resources), while more than 7000 plant plastid genomes have been assembled and published to date (accessed on Jan. 18, 2022). Advancements in sequencing technologies and subsequently applied assembly algorithms have resulted in abundant plant mitogenomes (especially for closely related plants), which could contribute to revealing the evolutionary mechanisms of mitogenomes [3] and the domestication history of plants [4].

Plant mitogenomes vary in size but show conserved gene contents. For example, a core set of 24 protein-coding genes are generally shared among angiosperm mitogenomes [5], whereas the mitogenome length varies from 66 kb in Viscum scurruloideum Barlow [6] to 11.3 Mb in Silene conica L. [7]. RNA editing can result in amino acid sequences that differ from the corresponding conserved gene templates, which is often pervasive in the mitochondria of diverse eukaryotes (especially in land plants, [8,9,10]) and frequently causes the conversion of cytosine to uridine [8, 9, 11]. Another essential characteristic of plant mitogenomes is the great variation in their structures and noncoding contents [1, 5, 12]. Plant mitogenomes contain orders of magnitude more noncoding nucleotides (including introns, repetitive elements, and foreign DNA) than their metazoan counterparts [13], which contribute to the large size or the size variation of plant mtDNA genomes. First, mitochondrial introns in vascular plants play essential roles in the regulation of mitochondrial genes, which can reach 11.4 kb in Nymphaea colorata [14]. Group II introns are particularly prevalent within plant mitogenomes; these introns form a lariat-like structure via splicing, in contrast to group I introns. Second, the presence of repeats of various sizes in plant mitogenomes may result in high rates of genome rearrangements and even promote alternative genomic forms via recombination [12]. Third, the uptake of foreign sequences from the nuclear and plastid genomes is a vital source of noncoding sequences and might contribute to angiosperm mitogenome size expansion. For example, mitochondrial plastid sequences (MTPTs), which were first identified in maize, contribute 1 to 10% of the mitochondrial genomes of higher plants [15]. The majority of MTPTs are nonfunctional, with the exception of several tRNA genes and partial genes such as ccmC in Vitis vinifera [16]. In addition, a large plant mitogenome often includes larger mitochondrial nuclear DNA sequences (NUMTs). For example, approximately 20 and 33% of mtDNA was shown to be imported from the nucleus in apple [17] and watermelon [18], respectively. In short, the exploration of these noncoding sequences is essential to reveal the evolution of plant mitogenomes.

To date, most plant mitogenomes have been reconstructed as master circles containing the complete mitochondrial gene set [1, 7, 19,20,21]. Several hypotheses have been proposed to explain the size and/or structural variations of plant mitogenomes, such as different DNA repair mechanisms [22] and the integration of foreign sequences [3, 23]. However, the mechanisms underlying genome size variation and rearrangements remain unclear due to the small number of publicly available mitogenomes in plants [24,25,26].

The genus Primula L. (Primulaceae, Ericales) is an important ornamental and alpine plant group comprising more than 500 species worldwide [27,28,29]. The genus Primula has experienced rapid radiation (~ 30 Mya, [30]) and is mainly distributed in two geographically distant hotspots, the Himalaya–Hengduan Mountains in Asia and the Caucasus-Alps-Pyrenees regions in Europe [29]. The mechanisms underlying mitogenome evolution remain largely unknown because of the scarcity of well-studied mitochondrial data in Primula compared with the continuing progress in understanding nuclear and plastid genomes [31,32,33]. To our knowledge, only the Aegiceras corniculatum (L.) Blanco mitogenome from the family Primulaceae has been assembled thus far [34]. Thus, mitogenomes of species within Primula should be further studied, which may facilitate the discovery of their evolutionary dynamics on different scales, such as at the genus, family, or order level.

In this study, we aimed to explore the evolutionary history of mitogenomes among three Primula taxa: Primula valentiniana Hand.-Mazz., Primula smithiana Craib, and Primula palinuri Petagna. The first two species are restricted to alpine regions of the Himalaya–Hengduan Mountains. In contrast, P. palinuri is endemic to southern Italy and is adapted to the Mediterranean climate. We first sequenced and assembled the complete mitogenomes and plastomes of the three Primula species. Sequence repeats, foreign DNA fragments, RNA editing sites, and structural variation were analyzed in the three assembled mitogenomes. We also compared the nucleotide diversity of Primula taxa with that of other plant lineages. In addition, we discuss the phylogenetic application of mitogenomes and the potential causes of size variation in Ericales mitogenomes. In conclusion, our study provides insights into how the mitogenome has evolved in Ericales.

Results

Complete mitogenome size and gene content

The master circles of the three Primula mitogenomes were successfully reconstructed using two strategies (details in the Methods). Several putative mitochondrial contigs were identified for the de novo assembly of the P. palinuri, P. valentiniana, and P. smithiana sequences (Table S1). Further extension and merging of these contig sequences generated complete mitogenomes with master circles of 407,597 bp, 349,360 bp, and 426,527 bp, respectively (Fig. 1; Table 1). These draft genomes were verified by complete read remapping and/or polymerase chain reaction (PCR) amplification, since all the target sequences in the merging region of raw contigs were confirmed (Fig. S1). These mitogenomes exhibited similar GC contents, ranging from 45.2 to 45.5% (Fig. 1; Table 1).

Fig. 1
figure 1

Information on the three Primula mitogenomes. The circular mitogenomes of Primula smithiana (orange), Primula palinuri (purple), and Primula valentiniana (blue) are illustrated as linear. The outer circle represents the gene and its location from outside to inside. Yellow indicates a protein-coding gene, black indicates a tRNA gene, and purple indicates a rRNA gene. The inner portion indicates mitogenome length, and the black part indicates MTPTs. The line diagrams in the inner circle represent the coverage and GC content per 500-bp window size. The innermost chord diagram represents the shared sequences between the three mitochondrial genomes, whereas the height of the histogram represents the length of each shared area

Table 1 General features of the three Primula mitogenomes

Thirty-eight protein-coding genes, three rRNA genes, and 19 tRNA genes were shared among the three species (Table S2). These results suggested that the three mitogenomes presented relatively conserved gene contents. Most protein-coding genes occurred in single copies within the three mitogenomes. However, atp8, cox1, cox3, nad4, rps10, sdh3, and sdh4 presented two gene copies in P. smithiana (Table S2). These mitogenomes also contained the same RNA genes (i.e., rrn5, rrn18, and rrn26). It was notable that although most of the 19 shared tRNA genes occurred in single copies, the P. smithiana mitogenome possessed two copies at the trnC-GCA, trnD-GUC, trnM-CAU, trnN-GUU, trnS-GCU, trnS-UGA, and trnY-GUA genes and four copies at the trnH-GUG gene. All Primula mitogenomes lacked the group I intron, whereas 30, 22, and 23 group II introns were identified in P. smithiana, P. palinuri, and P. valentiniana, respectively (Table 1).

RNA editing in Primula mitogenomes

The three mitogenomes exhibited similar editing site numbers predicted with the PREP-Mt server [35]. For example, P. palinuri, P. valentiniana, and P. smithiana contained 467, 460, and 456 C-U editing sites, respectively (Fig. 2a). Approximately 300 RNA editing sites occurred at the 2nd base of the codon in each of the three Primula species. In contrast, approximately 140 sites occurred at the 1st base of the codon (Fig. 2a). Although the RNA editing sites were not evenly distributed among coding genes, the hydrophobic properties of all proteins were increased after editing (Fig. 2b). These amino acid changes mainly involved Ser-Leu, Pro-Leu, Arg-Cys, Pro-Ser, and His-Tyr transitions (Fig. 2c). For example, the average hydrophobic character per site in ccmB increased from 0.28 to 0.93 (Fig. 2d).

Fig. 2
figure 2

RNA editing and its potential influence. a Numbers of RNA editing sites in the different codons of three Primula mitogenomes. b Proportion of edited sites in the protein. The number above the bar indicates the increase in hydrophobic character after RNA editing. The trans-spliced genes are not shown. c Average number of amino acid changes after RNA editing. d Hydrophobic character of ccmB. The blue dotted line represents the average score, whereas the red line represents the average score of predicted proteins

Two RNA editing sites in atp6 and ccmFc produced stop codons in all Primula taxa. An editing-derived stop codon resulted in a 107-bp deletion in atp6 (Fig. S2), and an RNA editing site occurred at the penultimate amino acid codon in ccmFc (Fig. S3). Notably, both editing sites were also found across the other eight Ericales mitogenomes (Figs. S23). The editing efficiency of the edited-introducing stop codon in atp6 ranged from 50% (C. sinensis) to 100% (R. simsii), suggesting effective termination. However, the editing efficiency for ccmFc was 0, indicating that the predicted RNA editing site was a false positive.

Repeats and foreign-derived sequence identification

The total length of repeat regions in the three Primula mitogenomes varied dramatically. The P. smithiana mitogenome contained repeats with a total length of 181,003 bp (Fig. 3a), accounting for over 30% of the whole mitogenome sequence. P. palinuri and P. valentiniana exhibited relatively compact mitogenomes with total repeat lengths of 8105 bp and 4036 bp, respectively (Fig. 3b-c). The Primula mitogenomes lacked large tandem repeats (Tables S35).

Fig. 3
figure 3

Repeat region and coordinate of the three longest shared regions among Primula mitogenomes. a Repeat sequences in Primula smithiana (orange). b Primula valentiniana (blue). c Primula palinuri (purple)

Eleven MTPTs were identified within the three Primula taxa, and seven were commonly identified in the three species (Table S6). In addition, MTPT2 and MTPT6 were specific to P. palinuri, whereas MTPT8 and MTPT9 were specific to P. smithiana and P. valentiniana. Only the first two largest MTPTs (MTPT7 and MTPT10, both longer than 500 bp) were extracted for further analysis, as the Primula mitogenomes lacked large MTPTs. The depths of these MTPTs ranged from 44× to 80×, whereas those of their plastid counterparts ranged from 147.5× to 828.5× (Fig. S4). The presence of the two MTPTs was further verified through PCR amplification (Fig. S1). The GC contents of MTPT7 were 38.5% (P. smithiana), 38.7% (P. valentiniana), and 40.9% (P. palinuri), whereas those of MTPT10 were approximately 50–51% among the three species.

The phylogenetic relationships indicated that MTPT7 might have experienced three independent transfer events (Fig. 4a). One may have occurred after the speciation of P. palinuri, as its MTPT7 was grouped with its plastid counterpart. In contrast, the other two were distributed at distant positions in the phylogenetic tree (Fig. 4a). In particular, MTPT7 occurred very recently, with a unique insertion (approximately 1000 bp, Fig. 4a) in P. palinuri, exhibiting a higher GC content (40.9%). The oldest MTPT7 event occurred around the time of divergence between Androsace L. and Bryocarpum Hook. f. & Thomson (Fig. 4a), whereas MTPT10 probably appeared before the diversification of Primula (Fig. 4b).

Fig. 4
figure 4

Phylogenetic relationship of MTPT7 (a) and MTPT10 (b). Bootstrap values (> 50) are shown above the branches. pt. and mt indicate plastid and mitochondrial sequences, respectively. The alignment result is shown in the middle, in which the number at the top represents the sequence site, and different colors distinguish all parts of the alignment

NUMTs were searched against the P. veris L. nuclear genome (GCA_000788445.1). The total length of nuclear-shared sequences ranged from 210 kb to 266 kb. The longest nuclear-shared sequence was 9928 bp, which occurred in P. smithiana (Table S7).

Locally collinear blocks and gene clusters in Primula mitogenomes

The locally collinear blocks (LCBs) are the conserved genomic sequences among all genomes, which is useful for mitogenome structural analysis and for constructing a robust phylogenetic topology [36]. The LCBs among the three Primula mitogenomes were scattered in the mitogenomes, and no specific conserved region was longer than 50 kb (Fig. 1; Fig. S5). Despite the relatively short shared regions, the total length of the shared regions was extremely long. The shared sequences between P. smithiana and P. valentiniana were over 364 kb in length, which was markedly longer than in the other species pairs [P. smithiana and P. palinuri (288 kb), and P. valentiniana and P. palinuri (243 kb), Fig. 1].

Among the 29 conserved gene clusters identified in angiosperms [25], the three Primula mitogenomes possessed 13 of these shared gene clusters, whereas P. palinuri exhibited one additional gene cluster (>trnI-CAT > <trnD-GTC<) (Fig. S6). Eight additional gene clusters were also identified, four of which were specific to Primula compared to the other Ericales mitogenomes (Fig. 5; Fig. S7). Among the four specific gene clusters, each of the three gene clusters [nad9-trnW (CGA)-trnA (UGC) and rps12-nad3-trnM (CAU)] contained two (trnW-CGA and trnA-UGC) and one (trnM-CAU) plastid-derived gene, respectively.

Fig. 5
figure 5

Phylogenetic relationships of 11 Ericales mitogenomes based on 13 shared protein-coding genes. The support values are illustrated on the branches (left: the ultrafast bootstrap of the ML tree; right: the posterior probability of Bayesian inference). The dot plot represents the gene content in each mitogenome; however, genes shared by all mitogenomes or only lost in one are not illustrated. The rectangle represents the eight gene clusters identified in the three Primula mitogenomes, with C1-C8 representing cluster 1-cluster 8 (detailed information on each cluster is illustrated in Fig. S7). White and gray rectangles represent the loss and retention of these clusters

Nucleotide diversity based on locally collinear blocks of mitogenomes

The nucleotide diversity (π) of LCBs was calculated for different plant lineages (Table S8). First, Primula mitogenomes exhibited relatively high nucleotide diversity (π: 0.009) among all examined plant lineages, which was 10-fold higher than the lowest diversity, found in Zea (π: 0.0009) (Table S8). The π value (0.005) among the CDS regions of Primula was also higher than that in most of the analyzed taxa (Table S8). Second, the high nucleotide diversity at the genus level mainly contributed to the striking variation between P. palinuri (from the Mediterranean region) and the two alpine Primula taxa (from the Himalaya–Hengduan Mountains). The π value between the two alpine Primula taxa was 0.004, while the π value between the taxa from the two regions (i.e., the Himalaya–Hengduan Mountains and the Mediterranean regions) was 0.013 (Table S9).

Size variations and phylogenetic analyses among Ericales mitogenomes

The present study included eight published Ericales mitogenomes (from Primulaceae, Ericaceae, Actinidiaceae, and Theaceae) from NCBI, with the aim of revealing the potential causes of the observed mitogenome size variation at the order level (Table S10). The Monotropa hypopitys Crantz, Rhododendron simsii Planch., Actinidia argute Miq, Actinidia eriantha Benth., and Camellia sinensis (L.) Kuntze mitogenome sizes were 810 kb, 802 kb, 792 kb, 772 kb, and 707 kb, respectively, which were much larger than those of Vaccinium macrocarpon Aiton (459 kb), V. microcarpum Miyabe & T. Miyake (468 kb), Ae. corniculatum (425 kb), and the three Primula taxa (349–426 kb) (Fig. 6a). The total repeat lengths of R. simsii (343 kb), P. smithiana (181 kb), M. hypopitys (178), and C. sinensis (121 kb) were significantly larger than those of the remaining mitogenomes (each < 20 kb) (Fig. 6a). Most Ericales mitogenomes lacked large MTPTs, whereas total lengths of 21 kb and 41 kb were identified in Ac. arguta and Ac. eriantha, respectively (Fig. 6a).

Fig. 6
figure 6

Mitogenome sizes, repeats, MTPTs within Ericales, and their correlations. a Total length of different Ericales mitogenome components. b Proportions of different lengths of nuclear-shared sequences in Ericales mitogenomes. c Correlation of repeat and Ericales mitogenome size. The proportion started at 50% because most nuclear-shared sequences were < 500 bp. d Correlation of MTPTs and Ericales mitogenome size

Most Ericales NUMTs were < 500 bp, and the longest NUMT was identified in Ac. arguta (53 kb) (Fig. 6b). Additionally, there was a positive correlation between the NUMTs and Ericales mitogenome length, although the p value was slightly higher than 0.05 (Fig. S8). The relatively small mitogenome of Ae. corniculatum contained a large number of NUMTs (Table S10), which indicated that this species served as an outlier in this analysis. There was a very strong positive relationship between NUMTs and mitogenome sizes when Ae. corniculatum was removed (r2 = 0.55, P = 0.01, Fig. S9a). Pearson’s correlation test also indicated that repeats (Fig. 6c) were not significantly correlated with Ericales mitogenome size variation. However, a significant correlation was observed between repeats and mitogenome size when the kiwifruit mitogenomes were removed (Fig. S9b), since the large kiwifruit mitogenomes contained a small number of repeats [3]. There was also no significant relationship between MTPTs and mitogenome sizes in Ericales (Fig. 6d). R. simsii and M. hypopitys both showed relatively large mitogenomes but fewer MTPTs (Table S10). Therefore, the two species act as outliers in this analysis. There was a very strong positive relationship between MTPTs and mitogenome sizes when R. simsii and M. hypopitys were removed (r2 = 0.6, P = 0.01, Fig. S9c).

Protein-coding genes also varied within Ericales, and only 13 of these genes were shared among all eight Ericales taxa (Fig. 5). 38 protein-coding genes were shared between Primula taxa and Ae. corniculatum, whereas only 28 and 27 genes were observed in C. sinensis and Ac. arguta, respectively.

Both maximum likelihood (ML) and Bayesian inference trees were reconstructed based on the 13 shared protein-coding genes (with a total aligned length of 11,360 bp). Both trees suggested that P. smithiana (Sect. Proliferae) and P. valentiniana (Sect. Amethyatina) exhibited the closest relationship (Fig. 5). The interfamilial relationships (i.e., Primulaceae, Ericaceae, Actinidiaceae, and Theaceae) within Ericales species with available mitogenome data to date were resolved robustly. Primulaceae is sister to other families. Among the three other families, Theaceae was sister to a clade that contained Ericaceae and Actinidiaceae.

Discussion

Complete mitogenomes of three Primula taxa

The plant mitogenome is known for its considerable variation in both structure and content [1, 5, 12]. Most mitogenomes are reconstructed as a master circle containing the complete mitochondrial gene set [1, 7, 19,20,21]. A previously assembled pipeline [37,38,39] was followed to extend and merge the Primula mitochondrial contigs into a master circle. These master circles indicated highly homologous recombination (HR) frequencies, as no long collinear sequences were shared within Primula (Fig. S5) [3]. Most potential HR events occurred in the noncoding region and seemed to occur randomly among Primula mitogenomes, as no synteny could be detected based on the coordinates of each shared region (Fig. S5). Large repeats (> 500 bp) are often involved in reversible reciprocal HR that modulates plant mitogenome plasticity [25, 40, 41]. However, only the P. smithiana mitogenome exhibited a high proportion of repeats. As mitogenome reconstruction for P. palinuri and P. valentiniana involved the merging of several contigs, long repeats (over 30 kb in P. smithiana, Fig. 3a) might have been consolidated and eventually “vanished” from the final assemblies. This scenario could be examined using long-read sequencing technologies in the future.

Studies have discussed the subgenomic molecular forms of plant mitogenomes from linear branches to several circular sequences [42, 43]. The master circle reconstructed in the present study might not fully represent the only state of the Primula mitogenomes. However, the master circle contained all the mitochondrial genetic information [20, 23, 44]. The present study implemented two methods for confirming the reliability of our master circles. First, the clean reads were remapped against the master circle to identify potential assembly mistakes. Second, several PCR primer pairs were designed to verify the accuracy of the merging of contigs. The consecutive mapping and PCR results indicated the reliability of the master circles of the Primula mitogenomes (Fig. S1).

Contrasting patterns of nucleotide diversity across plant lineages

Compared with plant nuclear and plastid genomes, high rates of rearrangements in plant mitogenome frequently occur among closely related species [12]. Therefore, the conserved coding region and collinear segments might be relatively good resources for comparative analyses among different plant lineages [12, 20]. The study of mitochondrial collinear regions could further help us understand the evolution of plant mitogenomes [3, 36]. However, the lack of shared collinear fragments among plant lineages is due to frequent repeat-mediated rearrangement [12] and a lack of large collinear fragments, as shown in Picea [45].

In this study, we calculated and compared the nucleotide diversity of three collinear fragments of the mitogenomes within each genus (including at least three mitogenomes each). Primula mitogenomes exhibited the highest nucleotide diversity (Table S8), which was 2–3 times lower than the nucleotide diversity of the plastid genomes (complete sequence: 0.026; CDS: 0.019). This scenario is consistent with the synonymous-site divergence levels observed within the plastome and mitogenome [46].

There are several possible explanations for the contrasting patterns of nucleotide diversity within Primula and among plant lineages. First, Primula probably presents an elevated mutation rate in the mitogenome, as shown in several plant lineages [47]. Several functional genes might be positively selected by severe environmental conditions (such as strong ultraviolet radiation and extremely low temperatures in alpine environments) [48, 49], with far-reaching impacts on noncoding regions because of the hitchhiking effect. However, there is no clear evidence of elevated rates of mutation in these core genes. Second, a plausible alternative is that the LCB evolved under an assumed constant mutation rate, although substantial rate variation occurs among plant lineages. The specific evolutionary history of each plant genus should result in striking mitogenomic diversity. For example, the most recent common ancestor (MRCA) of the Primula taxa in the two regions (Europe vs. Asia) originated 20–40 Mya [30, 50], which is the oldest age among the taxa examined in this study, contributing to the accumulation of the greatest amount of nucleotide polymorphism. However, the MRCA of the two alpine Primula taxa in the Himalaya–Hengduan Mountains probably originated in the Late Miocene (approx. 9 Mya, [50]), resulting in approximately three times less nucleotide polymorphism than was observed between the two regions (Europe vs. Asia). At the other extreme, the genus Zea, which has diversified since approx. 0.18 Mya [51], presented the lowest interspecific polymorphism (Table S8). Third, the role of sampling error should be taken into account in considering these contrasting patterns of nucleotide polymorphism among plant lineages. Given that the LCB examined here accounted for a varying fraction of the whole mitogenome (4–64%), more LCB data and more comprehensive taxon sampling are required to test this in the future.

RNA editing is essential for mitochondrial gene expression

RNA editing is a common phenomenon within land plant mitogenomes involving the conversion of cytidines to uridines (C-U editing) or uridines to cytidines (U-C editing) in some plants [11, 52]. The most predictable RNA editing sites were located on the second codon in Primula, similar to most angiosperm mitogenomes [53].

Most of the predicted RNA editing sites could result in the conversion of the encoded amino acid from neutral to hydrophobic, ultimately increasing the hydrophobic character of the coding protein [53]. Hydrophobicity is conducive to protein folding and secondary structure formation [54]. The most frequent RNA editing events were found in ccmB and nad4L in P. smithiana. The secondary and tertiary structures of these two genes in P. smithiana showed increased stability of the protein.

In this study, only two RNA editing sites (in the atp6 and ccmFc genes) that could result in an early stop codon were identified in Primula, which is lower than the number found in kiwifruit mitogenomes [3]. Although both RNA editing sites could also be detected in other Ericales taxa (Figs. S23), only the termination in the atp6 gene was effective. The regulation of atp6 is essential for plant fertilization [55] and is related to cytoplasmic male sterility (CMS) in pepper [56], sunflower [57], rice [58], and Sorghum [59]. RNA editing in the atp6 gene also alters seed formation in maize [60]. Therefore, this RNA editing site in the atp6 gene may potentially impact the reproduction of Ericales species, but further studies are needed to verify this. Furthermore, our results highlight the importance of considering RNA editing sites during annotation.

Plastid-derived sequences in Primula mitogenomes

Transfer events from plastid to mitochondrial genomes frequently occur in angiosperm plants [61, 62]. Studies have revealed plastid-derived backgrounds of 0.1–11.5% of plant mitogenomes [63]. The present study identified 0.5–0.7% of Primula mitogenomes as MTPTs (Table 1).

MTPT transfer occurs independently among species [15], and plastid-derived fragments ultimately become nonfunctional pseudogenes [63]. Sequence transfer events from plastids to mitochondria inferred based on the oldest MTPT (trnV (uac)-trnM (cau)-atpE-atpB-rbcL) occurred at least 300 million years ago (Mya), before the divergence of extant gymnosperms and angiosperms [64]. In the present study, the oldest MTPT transfer events (MTPT7 and MTPT10) might date back to the divergence time of Primula and its relatives (approximately 23–40 Mya) (Fig. 4) [30]. However, a specific transfer event (such as MTPT7) probably occurred multiple times, as reported in several plant lineages [65].

Two hypotheses may explain the multiple transfer events observed. First, these transfer events could have been acquired directly via intracellular gene transfer (IGT). An ancient plastome-to-mitogenome transfer event occurred in ancestral species of Primula and its relatives but was partially lost in several species during the subsequent speciation process, after which IGT reoccurred recently. Second, the transfer event was acquired by plant-to-plant horizontal gene transfer (HGT). This means that the “ancient” MTPT was initially acquired via mitochondrion-to-mitochondrion HGT among plant taxa, rather than via an ancient plastid-to-mitochondrial IGT event [66]. Regardless, the underlying mechanism of MTPT deserves in-depth study in the future.

Phylogenetic implications from mitogenomes

Unlike plastid and nuclear genes (such as low copy nuclear genes or ITS), the mitogenome is not frequently used to reconstruct phylogenies or phylogeographies in higher plants due to its slow mutation rate [46], frequent genomic rearrangement [12], and incorporation of foreign DNA from the nuclear and plastid genomes [23]. However, several mitogenomic genes (such as atp1, matR, nad5, and rps3) have been widely used for plant phylogenetic studies at different levels since they may offer different insights than plastid and nuclear genes [67], see references therein). Theoretically, the coding genes of mitogenomes are more suitable for elucidating ancient diversification patterns in plants because of their generally slow mutation rates compared to plastid and nuclear genes [46].

In this study, the interfamilial relationships (i.e., Primulaceae, Ericaceae, Actinidiaceae, and Theaceae) within Ericales were resolved robustly based on the available mitogenome data (Fig. 5). Notably, these relationships are broadly consistent with previous studies with multiple fragment combinations (containing plastid, mitogenome, and nuclear genes [50];), plastomes [68], and transcriptomes and genomes [69, 70].

The three studied Primula taxa belong to two subgenera (Aleuritia and Auriculastrum) [28, 29]. Subgenus Aleuritia contains P. smithiana (Sect. Proliferae) and P. valentiniana (Sect. Amethyatina), whereas subgenus Auriculastrum includes P. palinuri (Sect. Auricula). Here, P. palinuri is sister to a clade that contains P. smithiana and P. valentiniana, consistent with the relationships based on plastid genes [30, 71].

The identified collinear gene clusters and LCB verified the above relationships in Primula. First, among 13 conserved mitochondrial gene clusters in Primula taxa (Fig. S6), one unique gene cluster (trnI-CAT-trnD-GTC) occurred only in P. palinuri. Second, the collinear fragments of the mitogenomes between P. smithiana and P. valentiniana exhibited lower nucleotide diversity than the other pairs containing P. palinuri (Table S9). The above two lines of evidence indicated the close relationship of P. smithiana and P. valentiniana. These results show that some conserved gene clusters and LCBs of plant mitogenomes present phylogenetic signals [36, 72].

Mitogenome size expansion in Ericales

Several hypotheses have been proposed to explain the considerable variation in mitogenome size observed in land plants [3, 13, 22, 23]. However, further specific studies are required [73]. The variation in noncoding sequences probably results in size variation [74], as most angiosperm mitogenomes generally contain a core set of 24 protein-coding genes [47], and 100-fold variation is observed among total plant mitogenome sizes [5].

The uptake of foreign sequences is a vital source of noncoding sequences [17, 23, 61, 75] and might contribute to angiosperm mitogenome size expansion. A large plant mitogenome often contains longer nuclear-shared sequences [76]. NUMT seems to contribute to mitogenome size in Ericales, despite the lack of a strong overall NUMT-mitogenome size relationship (Fig. S8). MTPT is also sometimes linked to the size variation of angiosperm mitogenomes [25, 77]. However, no significant relationship between MTPTs and mitogenome sizes was found in Ericales (Fig. S6d). The relatively large mitogenomes of R. simsii and M. hypopitys do not possess large MTPTs, probably because of the lack of an inverted repeat region (IR) in R. simsii [78] or because all genes encode products with photosynthetic functions and RNA polymerase subunits in the mycoheterotrophic plant M. hypopitys [79]. Collectively, the results indicated that the uptake of foreign sequences is a vital source of mitogenome size expansion within Ericales, albeit with some exceptions.

Repeats usually cause plant mitogenome size variation [20]. Approximately 42.7% of the R. simsii mitogenome consisted of repeat sequences, probably resulting in the largest mitogenome in Ericales. However, an exception was observed in the kiwifruit mitogenomes (Fig. 6c), which possessed large mitogenomes but lacked repeats [3], suggesting diverse reasons for mitogenome size variation in the Ericales order. Further studies are needed to examine plant mitogenome size expansion and variation.

Conclusions

This study successfully assembled the complete mitogenomes of three Primula species in the form of master circles. These mitogenomes shared similar gene contents but varied in structure. Relatively high nucleotide diversity was found in the Primula mitogenomes among all examined plant lineages. The RNA editing of these Primula mitogenomes could increase protein stability and alleviate the influence of amino acid mutation. MTPT events that co-occurred in the mitogenome and plastome were identified using the phylogenetic method, indicating that multiple transfer events probably occurred in the evolutionary history of Primula. In addition, mitogenomic genes, collinear gene clusters, and LCB all showed phylogenetic signals. Although the size of IGT events and repeats might drive mitogenome size variation in Ericales, the diverse reasons for mitogenome size variation in the order must be studied further.

Methods

Plant materials, DNA extraction, and sequencing

Fresh young leaves of P. smithiana (voucher no. Xu et al. 150,170) were collected from the South China Botanical Garden greenhouse, Chinese Academy of Sciences (Guangzhou, China), and cultivated from Yadong County of Tibet, China. Mitochondria were extracted from the leaves using density gradient centrifugation as described in a previous study [80]. mtDNA was extracted using the modified cetyltrimethylammonium bromide (CTAB) method [81]. Silica gel-dried leaves of P. valentiniana (voucher no. Hao et al. 120,274) were used for DNA extraction via the CTAB method [81]. The Kew DNA Bank provided the total DNA of P. palinuri (voucher no. Chase M.W. 16,567, Kew) (https://dnabank.science.kew.org). These voucher specimens were formally identified or checked by the third author (Prof. Gang Hao, South China Agricultural University) and deposited in the herbarium of the South China Botanical Garden, Chinese Academy of Sciences (IBSC). All experimental research complied with relevant institutional, national, and international guidelines and legislation. No specific permissions or licenses were required for our collection activities and experiments. A 250-bp paired-end library was prepared and sequenced on the Illumina HiSeq 2500 platform (Illumina, San Diego, CA, USA).

Genome assembly and validation

The short reads were checked using FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and trimmed using Trimmomatic [82] for the P. smithiana assembly. The clean reads were assembled de novo using Spades v3.13.0 [83], and putative contigs were then selected and extended using PRICE [84] with the following parameters: 600 95 -nc 50 -dbmax 72 -mol 30 -mpi 90 -target 90 2 1 1.

Genome skimming data for P. palinuri and P. valentiniana were used after quality control for de novo assembly by MEGAHIT v1.0 [85] and Spades v3.13.0 [83] to maximize the utilization of paired-end reads. Furthermore, the potential mitochondrial contigs were selected based on coverage and rechecked manually by BLASTN [86] against the NCBI nonredundant nucleotide database. The whole trimmed reads were then mapped to the putative mitogenome contigs with Geneious (http://www.geneious.com/). Contigs were extended based on the mapping coverage as described by Mower et al. [87] and Zhang et al. [39]. Mapped sequences were excluded if their sequencing coverage depth was < 5× and > 500× or the overlap was < 50 bp. In the continuous extension cycle, contigs showing overlap of greater than 80 bp and identity over 99% were merged.

The complete reads were aligned against these draft mitogenomes using BWA v0.7 [67] with the default parameters to evaluate the coverage consistency and read connectivity. The sites that differed from 75% of the other aligned reads were corrected.

Although several isoforms of angiosperm mitochondrial sequences have been reported, the assembled form of a master circle containing all mitochondrial genes is commonly found in various plant groups [1, 3, 5, 42]. To further check the reliability of our assembly, five PCR primer pairs were designed between two initial contigs for each species to confirm whether these assembled regions could be successfully amplified (Fig. S1; Table S11).

Annotation of Primula mitogenomes

Protein and rRNA genes were annotated using the GeSeq online server [88] and local BLASTN [86], with eight Ericales mitogenomes [Ae. Corniculatum (MT130509.1), R. simsii (MW030508.1), C. sinensis (NC_043914.1), V. macrocarpon (NC_023338.1), V. microcarpum (MK715445.1), M. hypopitys, (MK990822, MK990823), Ac. arguta (MH559343), and A. eriantha (MH645952.1)] as references. tRNAs were identified by using tRNAscan-SE v2.0.7 [89]. The start and stop codons in exons were adjusted manually. Group I and II introns were detected with the RNAweasel tool [90]. ORF-Finder was used for predicting open reading frames longer than 300 bp with the standard genetic code (https://www.ncbi.nlm.nih.gov/orffinder/). The GC count per 500 bp was calculated with an in-house Python3 script. The depth of sequencing coverage per locus was calculated using the genomecov command in bbMap (https://www.sourceforge.net/projects/bbmap/) with the parameter –d.

Repeat regions were identified by alignment against each assembly using BLASTN [86] with a minimum identity of 85% and a minimum length of 100 bp. Tandem repeat sequences were detected by using Tandem Repeats Finder [91] with the default parameters. The detailed information of the three Primula mitogenomes was visualized using Circos v0.69 [92].

Identification of RNA editing sites and gene clusters

RNA editing sites in the three mitogenomes were predicted using the PRET-Mt server [35] with a cutoff value of 0.2. The hydrophobicity of ccmB and nad4L in P. smithiana were calculated using ProtScale [93]. In contrast, the average hydrophobic character of P. smithiana protein-coding genes was calculated based on the method described by Kyte and Doolittle [94].

The atp6 and ccmFc gene sequences were extracted from the eight publicly available Ericales and Primula mitogenomes and were aligned using MAFFT v.7.4 [95]. The secondary structures of atp6 and ccmFc were inferred using PSIPRED [96]. To validate the predicted editing sites, the RNA-seq data of Ac. arguta (SRR3823655), Ae. Corniculatum (SRR1688722), C. sinensis (SRR20083852), M. hypopitys (SRR10159707), R. simsii (SRR10415549), and V. macrocarpon (SRR18449568) were downloaded from the NCBI SRA database and mapped to the atp6 and ccmFc gene sequences using BWA v0.7 [67]. Editing efficiency was estimated by calculating the proportion of cDNA reads that contained the edited nucleotide.

The 29 gene clusters in the plant mitogenomes described by Richardson et al. [97] were identified in the Ericales mitogenomes by manual inspection. Additional gene clusters were searched among Primula taxa through visual checking, as described by Kan et al. [25].

Identification of conserved sequences and foreign-shared sequences

Each pair of Primula mitogenomes was aligned against the others to identify LCBs using the nucmer command in MUMMER4 [98] under the default parameters. The aligned areas with lengths < 2000 bp were removed. To calculate the interspecific nucleotide diversity of mitogenomes in plant genera, more than three mitogenomes (from different species) within each genus were considered and retrieved from GenBank (Table S8). The top three LCB and their CDSs within each genus were aligned using MAFFT v7.4 [95] and then concentrated using SequenceMatrix [99]. Nucleotide diversity was calculated using DnaSP v.6 [100].

Three Primula plastid genomes were assembled using GetOrganelle [101] and annotated using the GeSeq server [88]. Transfer events were identified by aligning each Primula mitogenome against the P. palinuri plastid genome (after removing one inverted repeat) using local BLASTN with a minimum length of 100 bp and an e-value of 1e-20. Putative MTPTs, including atp1/atpA, rrn26/rrn23, and rrn18/rrn16, were excluded because they simultaneously occurred in the mitogenome and plastid genome [20, 25, 66].

Two MTPTs longer than 500 bp (containing enough polymorphic variation for phylogenetic analysis) were extracted and validated using read mapping and PCR amplification. Each clean read was mapped against the 100 bp up- and downstream regions of MTPT in the mitogenome and its plastid genome counterpart for read mapping. MTPT7 and MTPT10 were aligned with the other 30 publicly available plastid genomes (Table S12) after validation within Primulaceae using MAFFT v7.4 [95]. Each aligned region was trimmed using Gblocks [102]. IQ-TREE v1.6.12 [103] was used to construct an ML tree with 5000 ultrafast bootstrapping replicates under the best model detected using ModelFinder [104]. Then, the GC content of the two sequences was calculated using an in-house Python3 script.

To account for gene transfer events between the mitogenome and nuclear genome, the nuclear-shared sequences were identified by aligning each Primula mitogenome against the P. veris nuclear genome (GCA_000788445.1) using BLASTN with a minimum length of 50 bp and an e-value of 1e-20. The nuclear-shared regions in other Ericales mitogenomes were also identified against their corresponding nuclear genomes. This reference nuclear genome information can be found in Table S13. The size information of mitogenomes, repeats, MTPTs, and NUMTs can be found in Table S10.

Repeat regions and MTPTs were also identified among Ericales mitogenomes. Pearson’s correlation was calculated between repeats, NUMTs, MTPTs, and mitogenome size in Ericales to reveal the underlying causes of mitogenome size variation [3].

Phylogenetic analysis and identification of the contents of Ericales mitogenomes

The above eight publicly available Ericales mitogenomes and three Primula mitogenomes (representing Primulaceae, Ericaceae, Actinidiaceae, and Theaceae) were included in the phylogenetic analysis, with Platycodon grandiflorus A. DC. (NC_035958.1; Campanulaceae) and Solanum lycopersicum L. (NC_035963.1; Solanaceae) as outgroups. A total of 13 coding sequences (CDSs) among the mitogenomes were aligned with MAFFT v7.4 [95]. Conserved aligned regions were extracted with Gblocks [102] and concatenated with SequenceMatrix [99]. ML phylogenetic trees were built using IQ-TREE v1.6.12 [103] with 5000 ultrafast bootstrapping replicates under the GTR + G model. Bayesian inference was conducted using MrBayes v3.2 [105] under the GTR + G + F model. The Markov chain Monte Carlo (MCMC) algorithm was run for 2.0 × 107 generations with four incrementally heated chains, starting from random trees and sampling one out of every 1000 generations. The stability of the Markov chain was ascertained by plotting likelihood values against the number of generations (effective sample size > 200) using Tracer v1.7 [106] and by splitting variances < 0.01. The burn-in fraction was set to 0.25, and the remaining trees were used to construct the 50%-majority rule consensus tree. Bayesian posterior probabilities were used to estimate support for each branch in the consensus tree.

Availability of data and materials

The data of this study have been deposited in the NCBI with BioProject accession number PRJNA794031. The genome skimming sequencing reads can be found under the number SRR17422315-SRR17422317. Mitogenome assembly of Primula has been deposited to GenBank with accession numbers OM971881-OM971883. Plastid genomes of three Primula taxa have been deposited to GenBank with accession numbers OM313289-OM313291.

Abbreviations

bp:

base pair

CDS:

Coding sequence

DNA:

Deoxyribo Nucleic acid

GC:

Guanine- cytosine

HGT:

Horizontal gene transfer

HR:

Homologous rearrangement

kb:

kilobase

LCB:

Locally collinear blocks

MTPT:

Mitochondrial plastid DNA

ML:

Maximum likelihood

mtDNA:

mitochondrial DNA

NUMT:

Nuclear mitochondrial DNA sequences

IGT:

Intracellular gene transfer

ORF:

Open reading frame

PCR:

Polymerase chain reaction

RNA:

Ribonucleic acid

atp1, atp4, atp6, atp8 and atp9:

Genes for ATP synthase subunits 1, 4, 6, 8 and 9

ccmC, ccmC, ccmFc and ccmFn:

Genes for cytochrome c biogenesis proteins B, C, Fc and Fn

cob:

Gene for cytochrome b

cox1, cox2 and cox3:

Genes for cytochrome c oxidase subunits 1, 2 and 3

matR:

Gene for maturase

mttB:

transport membrane protein B

nad1, nad2, nad3, nad4, nad4L, nad5, nad6, nad7 and nad9:

Mitochondrial genes for NADH dehydrogenase subunits 1–7, 9 and 4 L

rpl2, rpl5 and rpl16:

Genes for ribosomal proteins L2, L5 and L16

rps1, rps2, rps3, rps4, rps7, rps10, rps11, rps12, rps13, rps14 and rps19:

Genes for ribosomal proteins S1, S2, S3, S4, S7, S10, S11, S12, S13, S14, and S19

sdh3 and sdh4:

Genes for succinate dehydrogenase cytochrome subunits 3 and 4

trnL:

tRNA gene for leucine

trnT:

tRNA gene for threonine

trnS:

tRNA gene for serine

Arg:

Arginine

Cys:

L-cysteine

His:

Histidine

Pro:

Proline

Ser:

Serine

Tyr:

Tyrosine

References

  1. Gualberto JM, Newton KJ. Plant mitochondrial genomes: dynamics and mechanisms of mutation. Annu Rev Plant Biol. 2017;68(1):225–52.

    Article  CAS  PubMed  Google Scholar 

  2. Schleicher S, Binder S. In Arabidopsis thaliana mitochondria 5′ end polymorphisms of nad4L-atp4 and nad3-rps12 transcripts are linked to RNA PROCESSING FACTORs 1 and 8. Plant Mol Biol. 2021;106(4–5):335–48.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Wang S, Li D, Yao X, Song Q, Wang Z, Zhang Q, et al. Evolution and diversification of kiwifruit mitogenomes through extensive whole-genome rearrangement and mosaic loss of intergenic sequences in a highly variable region. Genome Biol Evol. 2019;11(4):1192–206.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Diaz-Garcia L, Rodriguez-Bonilla L, Rohde J, Smith T, Zalapa J. Pacbio sequencing reveals identical organelle genomes between American cranberry (Vaccinium macrocarpon Ait.) and a wild relative. Genes. 2019;10(4):291.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Zardoya R. Recent advances in understanding mitochondrial genome diversity. F1000Res. 2020;9:270.

    Article  CAS  Google Scholar 

  6. Skippington E, Barkman TJ, Rice DW, Palmer JD. Miniaturized mitogenome of the parasitic plant Viscum scurruloideum is extremely divergent and dynamic and has lost all nad genes. Proc Natl Acad Sci U S A. 2015;112(27):E3515–E24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Putintseva YA, Bondar EI, Simonov EP, Sharov VV, Oreshkova NV, Kuzmin DA, et al. Siberian larch (Larix sibirica Ledeb.) mitochondrial genome assembled using both short and long nucleotide sequence reads is currently the largest known mitogenome. BMC Genomics. 2020;21:654.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Covello PS, Gray MW. RNA editing in plant mitochondria. Nature. 1989;341(6243):662–6.

    Article  CAS  PubMed  Google Scholar 

  9. Castandet B, Araya A. RNA editing in plant organelles. Why make it easy? Biochem Mosc. 2011;76(8):924–31.

    Article  CAS  Google Scholar 

  10. Small ID, Schallenberg-Rüdinger M, Takenaka M, Mireau H, Ostersetzer-Biran O. Plant organellar RNA editing: what 30 years of research has revealed. Plant J. 2020;101(5):1040–56.

    Article  CAS  PubMed  Google Scholar 

  11. Binder S, Marchfelder A, Brennicke A, Wissinger B. RNA editing in trans-splicing intron sequences of nad2 mRNAs in Oenothera mitochondria. J Biol Chem. 1992;267(11):7615–23.

    Article  CAS  PubMed  Google Scholar 

  12. Mower JP. Variation in protein gene and intron content among land plant mitogenomes. Mitochondrion. 2020;53:203–13.

    Article  CAS  PubMed  Google Scholar 

  13. Smith DR. The mutational hazard hypothesis of organelle genome evolution: 10 years on. Mol Ecol. 2016;25(16):3769–75.

    Article  PubMed  Google Scholar 

  14. Brown GG, Colas des Francs-Small C, Ostersetzer-Biran O. Group II intron splicing factors in plant mitochondria. Front Plant Sci. 2014;5:35.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Wang X, Chen H, Yang D, Liu C. Diversity of mitochondrial plastid DNAs (MTPTs) in seed plants. Mitochondrial DNA A DNA Mapp Seq Anal. 2017;29(4):635–42.

    PubMed  Google Scholar 

  16. Wang D, Rousseau-Gueutin M, Timmis JN. Plastid sequences contribute to some plant mitochondrial genes. Mol Biol Evol. 2012;29(7):1707–11.

    Article  CAS  PubMed  Google Scholar 

  17. Goremykin VV, Salamini F, Velasco R, Viola R. Mitochondrial DNA of Vitis vinifera and the issue of rampant horizontal gene transfer. Mol Biol Evol. 2008;26(1):99–110.

    Article  PubMed  Google Scholar 

  18. Cui H, Ding Z, Zhu Q, Wu Y, Qiu B, Gao P. Comparative analysis of nuclear, chloroplast, and mitochondrial genomes of watermelon and melon provides evidence of gene transfer. Sci Rpt. 2021;11:1595.

    CAS  Google Scholar 

  19. Goremykin VV, Lockhart PJ, Viola R, Velasco R. The mitochondrial genome of Malus domestica and the import-driven hypothesis of mitochondrial genome expansion in seed plants. Plant J. 2012;71(4):615–26.

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  21. Kovar L, Nageswara-Rao M, Ortega-Rodriguez S, Dugas DV, Straub S, Cronn R, et al. PacBio-based mitochondrial genome assembly of Leucaena trichandra (Leguminosae) and an Intrageneric assessment of mitochondrial RNA editing. Genome Biol Evol. 2018;10(9):2501–17.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  PubMed Central  Google Scholar 

  23. Alverson AJ, Wei X, Rice DW, Stern DB, Barry K, Palmer JD. Insights into the evolution of mitochondrial genome size from complete sequences of Citrullus lanatus and Cucurbita pepo (Cucurbitaceae). Mol Biol Evol. 2010;27(6):1436–48.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Choi I, Ruhlman TA, Jansen RK. Comparative mitogenome analysis of the genus Trifolium reveals independent gene fission of ccmFn and intracellular gene transfers in Fabaceae. Int J Mol Sci. 2020;21(6):1959.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Kan SL, Shen TT, Gong P, Ran JH, Wang XQ. The complete mitochondrial genome of Taxus cuspidata (Taxaceae): eight protein-coding genes have transferred to the nuclear genome. BMC Evol Biol. 2020;20:10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Makarenko MS, Omelchenko DO, Usatov AV, Gavrilova VA. The insights into mitochondrial genomes of sunflowers. Plants. 2021;10(9):1774.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Basak SK, Maiti G, Hajra PK. The genus Primula L. in India (a taxonomic revision). Dehradun: Bishen Singh Mahendra Pal Singh; 2014.

    Google Scholar 

  28. Hu CM, Kelso S. Primulaceae. In: Wu ZY, Raven PH, editors. Flora of China (Vol 15). St. Louis: Science Press, Beijing & Missouri Botanical Garden Press; 1996.

    Google Scholar 

  29. Richards J. Primula. Portland: Timber Press; 2003.

    Google Scholar 

  30. De Vos JM, Hughes CE, Schneeweiss GM, Moore BR, Conti E. Heterostyly accelerates diversification via reduced extinction in primroses. Proc Biol Sci. 2014;281(1784):20140075.

    PubMed  PubMed Central  Google Scholar 

  31. Cocker JM, Wright J, Li J, Swarbreck D, Dyer S, Caccamo M, et al. Primula vulgaris (primrose) genome assembly, annotation and gene expression, with comparative genomics on the heterostyly supergene. Sci Rpt. 2018;8(1):17942.

    CAS  Google Scholar 

  32. Nowak MD, Russo G, Schlapbach R, Huu CN, Lenhard M, Conti E. The draft genome of Primula veris yields insights into the molecular basis of heterostyly. Genome Biol. 2015;16(1):12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Ren T, Yang Y, Zhou T, Liu Z. Comparative plastid genomes of Primula species: sequence divergence and phylogenetic relationships. Int J Mol Sci. 2018;19(4):1050.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Zhang J, Zhang S, Zhang Y. The complete mitochondrial genome of a mangrove plant: Aegiceras corniculatum and its phylogenetic implications. Mitochondrial DNA B Resour. 2020;5(2):1502–3.

    Article  Google Scholar 

  35. Mower JP. The PREP suite: predictive RNA editors for plant mitochondrial genes, chloroplast genes and user-defined alignments. Nucleic Acids Res. 2009;37:W253–W59.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Wang S, Song Q, Li S, Hu Z, Dong G, Song C, et al. Assembly of a complete mitogenome of Chrysanthemum nankingense using Oxford Nanopore long reads and the diversity and evolution of Asteraceae mitogenomes. Genes. 2018;9(11):547.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Wang X, Bi C, Xu Y, Wei S, Dai X, Yin T, et al. The whole genome assembly and comparative genomic research of Thellungiella parvula (extremophile crucifer) mitochondrion. Int J Genomics. 2016;2016:1–13.

    Google Scholar 

  38. Wang X, Cheng F, Rohlsen D, Bi C, Wang C, Xu Y, et al. Organellar genome assembly methods and comparative analysis of horticultural plants. Hortic Res. 2018;5(1):3.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Zhang R, Jin J, Moore MJ, Yi TS. Assembly and comparative analyses of the mitochondrial genome of Castanospermum australe (Papilionoideae, Leguminosae). Aust Syst Bot. 2019;32:484–94.

    Google Scholar 

  40. Chevigny N, Schatz-Daas D, Lotfi F, Gualberto JM. DNA repair and the stability of the plant mitochondrial genome. Int J Mol Sci. 2020;21(1):328.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Štorchová H, Stone JD, Sloan DB, Abeyawardana OAJ, Müller K, Walterová J, et al. Homologous recombination changes the context of cytochrome b transcription in the mitochondrial genome of Silene vulgaris KRA. BMC Genomics. 2018;19:874.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Kozik A, Rowan BA, Lavelle D, Berke L, Schranz ME, Michelmore RW, et al. The alternative reality of plant mitochondrial DNA: one ring does not rule them all. PLoS Genet. 2019;15(8):e1008373.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Yu R, Sun C, Zhong Y, Liu Y, Sanchez Puerta MV, Mower JP, et al. The minicircular and extremely heteroplasmic mitogenome of the holoparasitic plant Rhopalocnemis phalloides. Curr Biol. 2022;32(2):470–79.e5.

    Article  CAS  PubMed  Google Scholar 

  44. Palmer JD, Shields CR. Tripartite structure of the Brassica campestris mitochondrial genome. Nature. 1984;307(5950):437–40.

    Article  CAS  Google Scholar 

  45. Sullivan AR, Eldfjell Y, Schiffthaler B, Delhomme N, Asp T, Hebelstrup KH, et al. The mitogenome of Norway spruce and a reappraisal of mitochondrial recombination in plants. Genome Biol Evol. 2020;12(1):3586–98.

    Article  CAS  PubMed  Google Scholar 

  46. Wolfe KH, Li WH, Sharp PM. Rates of nucleotide substitution vary greatly among plant mitochondrial, chloroplast, and nuclear DNAs. Proc Natl Acad Sci U S A. 1987;84(24):9054–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Sloan DB, Müller K, McCauley DE, Taylor DR, Štorchová H. Intraspecific variation in mitochondrial genome sequence, structure, and gene content in Silene vulgaris, an angiosperm with pervasive cytoplasmic male sterility. New Phytol. 2012;196(4):1228–39.

    Article  CAS  PubMed  Google Scholar 

  48. Sinha RP, Hader DP. UV-induced DNA damage and repair: a review. Photochem Photobiol Sci. 2002;1(4):225–36.

    Article  CAS  PubMed  Google Scholar 

  49. He X, Burgess KS, Gao LM, Li DZ. Distributional responses to climate change for alpine species of Cyananthus and Primula endemic to the Himalaya-Hengduan Mountains. Plant Divers. 2019;41(1):26–32.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Rose JP, Kleist TJ, Lofstrand SD, Drew BT, Schonenberger J, Sytsma KJ. Phylogeny, historical biogeography, and diversification of angiosperm order Ericales suggest ancient Neotropical and east Asian connections. Mol Phylogen Evol. 2018;122:59–79.

    Article  Google Scholar 

  51. Orton LM, Burke SV, Wysocki WP, Duvall MR. Plastid phylogenomic study of species within the genus Zea: rates and patterns of three classes of microstructural changes. Curr Genet. 2017;63(2):311–23.

    Article  CAS  PubMed  Google Scholar 

  52. Fan W, Guo W, Funk L, Mower JP, Zhu A. Complete loss of RNA editing from the plastid genome and most highly expressed mitochondrial genes of Welwitschia mirabilis. Sci China Life Sci. 2019;62(4):498–506.

    Article  CAS  PubMed  Google Scholar 

  53. He ZS, Zhu AD, Yang JB, Fan WS, Li DZ. Organelle genomes and transcriptomes of Nymphaea reveal the interplay between intron splicing and RNA editing. Int J Mol Sci. 2021;22(18):9842.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Li Z, Liu Z, Zhong W, Huang M, Wu N, Xie Y, et al. Large-scale identification of human protein function using topological features of interaction network. Sci Rpt. 2016;6(1):37179.

    CAS  Google Scholar 

  55. Zancani M, Braidot E, Filippi A, Lippe G. Structural and functional properties of plant mitochondrial F-ATP synthase. Mitochondrion. 2020;53:178–93.

    Article  CAS  PubMed  Google Scholar 

  56. Kim DH, Kim BD. The organization of mitochondrial atp6 gene region in male fertile and CMS lines of pepper (Capsicum annuum L.). Curr Genet. 2006;49(1):59–67.

    Article  CAS  PubMed  Google Scholar 

  57. Makarenko MS, Usatov AV, Tatarinova TV, Azarin KV, Logacheva MD, Gavrilova VA, et al. Characterization of the mitochondrial genome of the MAX1 type of cytoplasmic male-sterile sunflower. BMC Plant Biol. 2019;19(1):41–7.

    Google Scholar 

  58. Hu J, Yi R, Zhang H, Ding Y. Nucleo-cytoplasmic interactions affect RNA editing of cox2, atp6 and atp9 in alloplasmic male-sterile rice (Oryza sativa L.) lines. Mitochondrion. 2013;13(2):87–95.

    Article  CAS  PubMed  Google Scholar 

  59. Howad W, Kempken F. Cell type-specific loss of atp6 RNA editing in cytoplasmic male sterile Sorghum bicolor. Proc Natl Acad Sci U S A. 1997;94(20):11090–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Li X, Huang W, Yang H, Jiang R, Sun F, Wang H, et al. EMP 18 functions in mitochondrial atp6 and cox2 transcript editing and is essential to seed development in maize. New Phytol. 2019;221(2):896–907.

    Article  CAS  PubMed  Google Scholar 

  61. Rice DW, Alverson AJ, Richardson AO, Young GJ, Sanchez-Puerta MV, Munzinger J, et al. Horizontal transfer of entire genomes via mitochondrial fusion in the angiosperm Amborella. Science. 2013;342(6165):1468–73.

    Article  CAS  PubMed  Google Scholar 

  62. Sanchez-Puerta MV, Cho Y, Mower JP, Alverson AJ, Palmer JD. Frequent, phylogenetically local horizontal transfer of the cox1 group I intron in flowering plant mitochondria. Mol Biol Evol. 2008;25(8):1762–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Warren JM, Sloan DB. Interchangeable parts: the evolutionarily dynamic tRNA population in plant mitochondria. Mitochondrion. 2020;52:144–56.

    Article  CAS  PubMed  Google Scholar 

  64. Wang D, Wu YW, Shih ACC, Wu CS, Wang YN, Chaw SM. Transfer of chloroplast genomic DNA to mitochondrial genome occurred at least 300 Mya. Mol Biol Evol. 2007;24(9):2040–8.

    Article  CAS  PubMed  Google Scholar 

  65. Cummings MP, Nugent JM, Olmstead RG, Palmer JD. Phylogenetic analysis reveals five independent transfers of the chloroplast gene rbcL to the mitochondrial genome in angiosperms. Curr Genet. 2003;43(2):131–8.

    Article  CAS  PubMed  Google Scholar 

  66. Gandini CL, Sanchez-Puerta MV. Foreign plastid sequences in plant mitochondria are frequently acquired via mitochondrion-to-mitochondrion horizontal transfer. Sci Rpt. 2017;7(1):43402.

    CAS  Google Scholar 

  67. Qiu YL, Li LB, Wang B, Xue JY, Hendry TA, Li RQ, et al. Angiosperm phylogeny inferred from sequences of four mitochondrial genes. J Syst Evol. 2010;48(6):391–425.

    Article  Google Scholar 

  68. Yan MH, Fritsch PW, Moore MJ, Feng T, Meng AP, Yang J, et al. Plastid phylogenomics resolves infrafamilial relationships of the Styracaceae and sheds light on the backbone relationships of the Ericales. Mol Phylogen Evol. 2018;121:198–211.

    Article  Google Scholar 

  69. Larson DA, Walker JF, Vargas OM, Smith SA. A consensus phylogenomic approach highlights paleopolyploid and rapid radiation in the history of Ericales. Am J Bot. 2020;107(5):773–89.

    Article  PubMed  Google Scholar 

  70. Zhang L, Wu W, Yan HF, Ge XJ. Phylotranscriptomic analysis based on coalescence was less influenced by the evolving rates and the number of genes: a case study in Ericales. Evol Bioinforma. 2015;11(Suppl 1):81.

    Google Scholar 

  71. Mast AR, Kelso S, Conti E. Are any primroses (Primula) primitively monomorphic? New Phytol. 2006;171(3):605–16.

    Article  CAS  PubMed  Google Scholar 

  72. Dong S, Zhao C, Chen F, Liu Y, Zhang S, Wu H, et al. The complete mitochondrial genome of the early flowering plant Nymphaea colorata is highly repetitive with low recombination. BMC Genomics. 2018;19:614.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Alverson AJ, Zhuo S, Rice DW, Sloan DB, Palmer JD. The mitochondrial genome of the legume Vigna radiata and the analysis of recombination across short mitochondrial repeats. PLoS One. 2011;6(1):e16404.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Wynn EL, Christensen AC. Repeats of unusual size in plant mitochondrial genomes: identification, incidence and evolution. G3: Genes, Genom, Genet. 2019;9(2):549–59.

    Article  CAS  Google Scholar 

  75. Sloan DB, Wu Z. History of plastid DNA insertions reveals weak deletion and AT mutation biases in angiosperm mitochondrial genomes. Genome Biol Evol. 2014;6(12):3210–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Ko YJ, Kim S. Analysis of nuclear mitochondrial DNA segments of nine plant species: size, distribution, and insertion loci. Genomics Inform. 2016;14(3):90.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Petersen G, Cuenca A, Zervas A, Ross GT, Graham SW, Barrett CF, et al. Mitochondrial genome evolution in Alismatales: size reduction and extensive loss of ribosomal protein genes. PLoS One. 2017;12(5):e0177606.

    Article  PubMed  PubMed Central  Google Scholar 

  78. Xu J, Luo H, Nie S, Zhang RG, Mao JF. The complete mitochondrial and plastid genomes of Rhododendron simsii, an important parent of widely cultivated azaleas. Mitochondrial DNA Part B-Resour. 2021;6(3):1197–9.

    Article  Google Scholar 

  79. Liu XD, Liao XY, Chen DQ, Zheng Y, Yu X, Xu XY, et al. The complete chloroplast genome sequence of Monotropa uniflora (Ericaceae). Mitochondrial DNA Part B-Resour. 2020;5(3):3186–7.

    Google Scholar 

  80. Tanaka Y, Tsuda M, Yasumoto K, Yamagishi H, Terachi T. A complete mitochondrial genome sequence of Ogura-type male-sterile cytoplasm and its comparative analysis with that of normal cytoplasm in radish (Raphanus sativus L.). BMC Genomics. 2012;13(1):352.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Allen GC, Flores Vergara MA, Krasynanski S, Kumar S, Thompson WF. A modified protocol for rapid DNA isolation from plant tissues using cetyltrimethylammonium bromide. Nat Protoc. 2006;1(5):2320–5.

    Article  CAS  PubMed  Google Scholar 

  82. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19(5):455–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Ruby JG, Bellare P, Derisi JL. PRICE: software for the targeted assembly of components of (Meta) genomic sequence data. G3: Genes, Genom, Genet. 2013;3(5):865–80.

    Article  Google Scholar 

  85. Li DH, Luo RB, Liu CM, Leung CM, Ting HF, Sadakane K, et al. MEGAHIT v1.0: a fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods. 2016;102:3–11.

    Article  CAS  PubMed  Google Scholar 

  86. Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, et al. BLAST+: architecture and applications. BMC Bioinform. 2009;10(1):421.

    Article  Google Scholar 

  87. Mower JP, Sloan DB, Alverson AJ. Plant mitochondrial genome diversity: the genomics revolution. In: Springer Vienna; 2012. p. 123–144.

    Book  Google Scholar 

  88. Tillich M, Lehwark P, Pellizzer T, Ulbricht-Jones ES, Fischer A, Bock R, et al. GeSeq-versatile and accurate annotation of organelle genomes. Nucleic Acids Res. 2017;45(W1):W6–W11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Chan PP, Lowe TM. tRNAscan-SE: searching for tRNA genes in genomic sequences. Methods Mol Biol. 2019;1962:1–14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Lang BF, Laforest MJ, Burger G. Mitochondrial introns: a critical view. Trends Genet. 2007;23(3):119–25.

    Article  CAS  PubMed  Google Scholar 

  91. Benson G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 1999;27(2):573–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Krzywinski M, Schein J, Birol İ, Connors J, Gascoyne R, Horsman D, et al. Circos: an information aesthetic for comparative genomics. Genome Res. 2009;19(9):1639–45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Wilkins MR, Gasteiger E, Bairoch A, Jean-Charles; S, Williams KL, Appel RD, Hochstrasser DF. Protein identification and analysis tools in the ExPASy server. In: The proteomics protocols handbook: Humana Press; 2005. p. 531–52.

    Google Scholar 

  94. Kyte J, Doolittle RF. A simple method for displaying the hydropathic character of a protein. J Mol Biol. 1982;157(1):105–32.

    Article  CAS  PubMed  Google Scholar 

  95. Katoh K. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 2002;30(14):3059–66.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. McGuffin LJ, Bryson K, Jones DT. The PSIPRED protein structure prediction server. Bioinformatics. 2000;16(4):404–5.

    Article  CAS  PubMed  Google Scholar 

  97. Richardson AO, Rice DW, Young GJ, Alverson AJ, Palmer JD. The “fossilized” mitochondrial genome of Liriodendron tulipifera: ancestral gene content and order, ancestral editing sites, and extraordinarily low mutation rate. BMC Biol. 2013;11(1):29.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Marçais G, Delcher AL, Phillippy AM, Coston R, Salzberg SL, Zimin A. MUMmer4: a fast and versatile genome alignment system. PLoS Comp Biol. 2018;14(1):e1005944.

    Article  Google Scholar 

  99. Vaidya G, Lohman DJ, Meier R. SequenceMatrix: concatenation software for the fast assembly of multi-gene datasets with character set and codon information. Cladistics. 2011;27(2):171–80.

    Article  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  101. Jin JJ, Yu WB, Yang JB, Song Y, Depamphilis CW, Yi TS, et al. GetOrganelle: a fast and versatile toolkit for accurate de novo assembly of organelle genomes. Genome Biol. 2020;21:241.

    Article  PubMed  PubMed Central  Google Scholar 

  102. Talavera G, Castresana J. Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments. Syst Biol. 2007;56(4):564–77.

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Ronquist F, Teslenko M, Van Der Mark P, Ayres DL, Darling A, Höhna S, et al. MrBayes 3.2: efficient bayesian phylogenetic inference and model choice across a large model space. Syst Biol. 2012;61(3):539–42.

    Article  PubMed  PubMed Central  Google Scholar 

  106. Rambaut A, Drummond AJ, Xie D, Baele G, Suchard MA. Posterior summarization in bayesian phylogenetics using tracer 1.7. Syst Biol. 2018;67(5):901–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We would like to thank Drs. Bao-Sheng Wang, Zheng Li, and Lin-Feng Li for their valuable comments on the early version of the manuscript. We also thank Yu-Yin Zhou and Qiong Dong for helping with the PCR validation. Special thanks to Kew DNA Bank of the Royal Botanic Gardens (Richmond, London, UK) for kindly providing Primula palinuri DNA. We thank American Journal Experts (AJE) for its linguistic assistance during the preparation of this manuscript.

Funding

This work was financially supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDB31000000) through Xue-Jun Ge and the National Natural Foundation of China (Grant No. 31870192) through Hai-Fei Yan.

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Authors and Affiliations

Authors

Contributions

TJL and HFY conceived this study. LW and TJL performed the analysis. LW conducted the experimental study. LW and TJL wrote the manuscript. HFY, XJG, and GH contributed feedback and edits to the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Tong-Jian Liu or Hai-Fei Yan.

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Supplementary Information

Additional file 1: 

Figure S1. Electrophoretic gel visualization of the amplified fragments of the three draft mitogenome assemblies and MTPTs. M1 is the DL2000 DNA marker, whereas M2 is the DL1000 DNA marker. The first two wells in each gel represent the corresponding primer pairs for MTPT7 and MTPT10 in each Primula mitogenome, whereas the other primer pairs were used for assembly validation in each draft mitogenome (primer details can be found in Table S11).

Additional file 2: 

FigureS2. The inferred secondary structure of the atp6 gene among the Ericales mitogenomes. Primula contains three Primula mitogenomes; Actinidia contains two kiwifruit mitogenomes.

Additional file 3: 

FigureS3. The inferred secondary structure of the ccmFc gene among the Ericales mitogenomes. Primula contains three Primula mitogenomes; Actinidia contains two kiwifruit mitogenomes.

Additional file 4: 

FigureS4. Average coverage of MTPTs and their plastid counterparts.

Additional file 5: 

Figure S5. The three longest LCBs and their distribution in Primula taxa.

Additional file 6: 

FigureS6. Gene clusters of each Ericales mitogenome. The red cell indicates the existence of one specific gene cluster.

Additional file 7: 

Figure S7. The newly identified gene clusters of each Ericales mitogenome. The red cell indicates the existence of one specific gene cluster.

Additional file 8: Figure S8.

Correlation of NUMT length and Ericales mitogenome size.

Additional file 9: Figure S9.

Correlation of NUMTs, MTPTs, and repeat length and Ericales mitogenome size after removing outlier mitogenomes. (a) NUMT length and Ericales mitogenome size after removing the Aegiceras corniculatum mitogenome; (b) repeat length and Ericales mitogenome size after removing the kiwifruit mitogenomes; (c) MTPT length and Ericales mitogenome size after removing the Rhododendron simsii and Monotropa hypopitys mitogenomes.

Additional file 10: 

Table S1. Assembly information of three Primula taxa. Table S2. The number of protein-coding genes in the three Primula mitogenomes. Table S3. Tandem repeats in the Primula smithiana mitogenome. Table S4. Tandem repeats in the Primula palinuri mitogenome. Table S5. Tandem repeats in the Primula valentiniana mitogenome. Table S6. Information on MTPTs within the three Primula mitogenomes. Table S7. The shared nuclear sequences within the three Primula mitogenomes. Table S8. The nucleotide diversity of mitogenomes within different plant lineages. Table S9. The nucleotide diversity of mitogenomes among Primula taxa. Table S10. The general features of the 11 mitogenomes used for this study. Table S11. The primers used for Primula palinuri, Primula smithiana, and Primula valentiniana. Table S12. The 30 publicly available plastid genomes used for MTPT analysis. Table S13. The publicly available nuclear genomes used for NUMT analysis.

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Wei, L., Liu, TJ., Hao, G. et al. Comparative analyses of three complete Primula mitogenomes with insights into mitogenome size variation in Ericales. BMC Genomics 23, 770 (2022). https://doi.org/10.1186/s12864-022-08983-x

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