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Assembly and analysis of the
mitochondrial genome of
Prunella vulgaris
Zhihao Sun
1
,YaWu
1
, Pengyu Fan
2
, Dengli Guo
2
, Sanyin Zhang
3
and Chi Song
1
*
1
Institute of Herbgenomics, Chengdu University of Traditional Chinese Medicine, Chengdu, China,
2
Wuhan Benagen Technology Co., Ltd, Wuhan, Hubei, China,
3
Innovative Institute of Chinese
Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, China
Prunella vulgaris (Lamiaceae) is widely distributed in Eurasia. Former studies have
demonstrated that P. vulgaris has a wide range of pharmacological effects.
Nevertheless, no complete P. vulgaris mitochondrial genome has been
reported, which limits further understanding of the biology of P. vulgaris. Here,
we assembled the first complete mitochondrial genome of P. vulgaris using a
hybrid assembly strategy based on sequencing data from both Nanopore and
Illumina platforms. Then, the mitochondrial genome of P. vulgaris was analyzed
comprehensively in terms of gene content, codon preference, intercellular gene
transfer, phylogeny, and RNA editing. The mitochondrial genome of P. vulgaris
has two circular structures. It has a total length of 297, 777 bp, a GC content of
43.92%, and 29 unique protein-coding genes (PCGs). There are 76 simple
sequence repeats (SSRs) in the mitochondrial genome, of which tetrameric
accounts for a large percentage (43.4%). A comparative analysis between the
mitochondrial and chloroplast genomes revealed that 36 homologous
fragments exist in them, with a total length of 28, 895 bp. The phylogenetic
analysis showed that P. vulgaris belongs to the Lamiales family Lamiaceae and P.
vulgaris is closely related to Salvia miltiorrhiza. In addition, the mitochondrial
genome sequences of seven species of Lamiaceae are unconservative in their
alignments and undergo frequent genome reorganization. This work reports for
the first time the complete mitochondrial genome of P. vulgaris, which provides
useful genetic information for further Prunella studies.
KEYWORDS
Prunella vulgaris, mitochondrial genome, codon usage, repeated sequence, evolution
1 Introduction
P. vulgaris is a low-growing herbaceous perennial widely distributed in Eurasia’s
temperate and tropical mountainous regions. The mature spikes of P. vulgaris are
cylindrical and slightly flat. Its stems are relatively short. The panicle consists of several
whorls of persistent calyxes and bracts, ranging from a few to ten. In southeastern China,
Frontiers in Plant Science frontiersin.org01
OPEN ACCESS
EDITED BY
Linchun Shi,
Chinese Academy of Medical Sciences and
Peking Union Medical College, China
REVIEWED BY
Yedomon Ange Bovys Zoclanclounon,
National Institute of Agricultural Sciences,
Republic of Korea
Muhammad Amjad Nawaz,
Far Eastern Federal University, Russia
*CORRESPONDENCE
Chi Song
songchi@cdutcm.edu.cn
RECEIVED 10 June 2023
ACCEPTED 17 July 2023
PUBLISHED 02 August 2023
CITATION
Sun Z, Wu Y, Fan P, Guo D, Zhang S and
Song C (2023) Assembly and analysis of the
mitochondrial genome of Prunella vulgaris.
Front. Plant Sci. 14:1237822.
doi: 10.3389/fpls.2023.1237822
COPYRIGHT
©2023Sun,Wu,Fan,Guo,ZhangandSong.
This is an open-access article distributed
under the terms of the Creative Commons
Attribution License (CC BY). The use,
distribution or reproduction in other
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accepted academic practice. No use,
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which does not comply with these terms.
TYPE Original Research
PUBLISHED 02 August 2023
DOI 10.3389/fpls.2023.1237822
the fresh leaves of P. vulgaris are served as a vegetable (Bai et al.,
2016). The spikes of dried fruits of P. vulgaris are considered to have
anti-inflammatory action in traditional Chinese medicine (Li et al.,
2015;Liu et al., 2020). Modern pharmacological studies have
revealed the presence of natural compounds with anti-
inflammatory, antibacterial, antioxidant, and immunomodulatory
properties in P. vulgaris, e.g., triterpenes, phenolic acid, and
oleanolic acid (Bai et al., 2016). These compounds are important
for pharmaceutical research (Su et al., 2022). The study of P.
vulgaris organelle genome is essential to better exploit its
medicinal and economic value. Important plastid organelles, i.e.,
mitochondria and chloroplast, play key roles in plant development
and reproduction, and their contributions to energy metabolism
and material conversion depend on their own semi-autonomous
genetic systems (Nielsen et al., 2010;Gualberto et al., 2014). Besides,
compared with whole genome assembly, the assembly of plastid
genome is more cost-effective and could provide useful information
for the evolutionary analysis of the focal species. The complete
chloroplast genome of P. vulgaris has already been assembled (Han
and Zheng, 2018). The present study reveals the complete
mitochondrial genome of P. vulgaris, providing the necessary
genetic sequence for further phylogeny and resource utilization.
As an important component of most eukaryotic cells,
mitochondria have energy conversion, biosynthetic, and signaling
functions. Mitochondria can encode some proteins semi-
autonomously, but these processes are regulated by nuclear-
encoded genes (Mackenzie and McIntosh, 1999). Thus, abnormal
mitochondrial gene expression in Brassica napus may lead to male
sterility(Liu et al., 2017). The characteristics of plant mitochondrial
genomes include the existence of highly conserved genes, a large
number of genomic structural rearrangements, a wide range of non-
coding sequences, and extensive RNA editing (Silvestris et al.,
2020). Mitochondrial genomes usually exhibit matrilineal
inheritance, which provides useful information about evolution
and phylogeny of the focal species (Birky, 2001). For example, the
mitochondrial genome sequence of Brassica oleracea facilitated the
evolutionary analysis of this species(Shao et al., 2021). The structure
of plant mitochondrial genomes may be linear or multi-branched
(Wang et al., 2019;Jackman et al., 2020). The reasons for the
structural diversity of plant mitochondrial genomes are still unclear.
The transfer of DNA between the mitochondrial genome and the
chloroplast genome is a common event in the plant genome. Some
studies believe that this event usually leads to changes in the length
of mitochondrial genome and changes the structure of
mitochondrial genome (Allen, 2015;Turmel et al., 2016). With
the rapid development of genome assembly and sequencing
technologies, complete organelle genomes of plants are able to be
assembled. This will facilitate our understanding of plants, for
example, by detecting nucleotide fragments of gene insertions or
deletions at the same position in different mitochondrial genomes
to distinguish species (Chen et al., 2022).
In this study, we assembled the first complete P. vulgaris
mitochondrial genome using a hybrid assembly strategy based on
sequencing data from Illumina and Nanopore. The assembled
mitochondrial genome was annotated from Illumina and
Nanopore platforms. The characteristic information of the
mitochondrial genome of P. vulgaris was discussed in terms of
codon usage preference, genome repeat sequence, and genes
transfer between the mitochondrial genome and chloroplast
genome. Phylogenetic tree and synteny analysis provide hints
about the evolutionary history of P. vulgaris. The results of this
study will provide useful information for the mitochondrial genome
of P. vulgaris.
2 Materials and methods
2.1 P. vulgaris DNA extraction and
mitochondrial genome assembly
The P. vulgaris plants were collected from wild in Hubei
province, China, and cultured in Wuhan, China (31°68’N, 118°
45’E). High quality genomic DNA were isolated from fresh leaves
using the standard CTAB method (Arseneau et al., 2017;Cheng
et al., 2021). Illumina and Nanopore platforms were used for
sequencing. Illumina sequencing and Oxford sequencing were
performed by Wuhan Benagen Tech Solutions Company (http://
en.benagen.com/). Illumina sequencing data was sequenced using
the HiSeq Xten PE150 Illumina, San Diego, CA, USA sequencing
platform and Nanopore sequencing was performed by Oxford
Nanopore GridION × 5 Oxford Nanopore Technologies, Oxford,
UK. GetOrganelle (v1.7.5) (Jin et al., 2020) was used to perform
plant mitochondrial genome assembly (default parameters) and a
graphical plant mitochondrial genome was obtained. Since the
graphical genome generated by GetOrganelle comprised multiple
nodes, with redundant fragments existing in the border of two
neighbor nodes, Bandage (Wick et al., 2015) was used to visualize
the graphical genome and Nanopore data was mapped to help
manually check these redundant fragments. BWA (0.7.17) is used to
map the third generation sequencing data to the graphical genome,
followed by manually identification and removing of the redundant
fragments (Li and Durbin, 2009).
2.2 Annotation of the mitochondrial
genome of P. vulgaris
The P. vulgaris mitochondrial genomes were annotated using
Geseq (Tillich et al., 2017) with Arabidopsis thaliana (Sloan et al.,
2018) and Liriodendron tulipifera (Richardson et al., 2013)as
reference genomes. The P. vulgaris mitochondrial genomes were
annotated using Geseq (Tillich et al., 2017). The tRNA genes were
annotated using the tRNAscan-SE (Lowe and Eddy, 1997). The
rRNA genes were annotated using BLASTN (Chen et al., 2015).
Each mitochondrial genome annotation error was manually
corrected using Apollo (Lewis et al., 2002).
2.3 Relative synonymous codon usage
The protein coding sequences of the genome were extracted
using Phylosuite (Zhang et al., 2020). Codon preferences of protein-
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coding genes in the mitochondrial genome were analyzed by Mega
(v7.0). The results of the analysis are expressed in relative
synonymous codon usage (RSCU).
2.4 Analysis of repeated sequences
The online version of MISA (Beier et al., 2017) was used to
analyze Simple Sequence Repeat (SSR) in assembled mitochondrial
genome. To define the SSR locus, we searched that SSRs with a
length of 1, 2, 3, 4, 5, and 6 bases have at least 10, 5, 4, 3, 3, and 3
repeats, respectively. The online version of TRF (Benson, 1999) was
used to identify tandem repeat sequences in the mitochondrial
genome, with alignment parameters: match = 2, mismatch = 5, and
indels = 7. REPuter web server (Kurtz et al., 2001) was used to
identify dispersed repeats with the following options: maximum
computed repeats = 5000, hamming distance = 3, and minimal
repeat size = 30.
2.5 Homologous fragments
between chloroplast genome
and mitochondrial genome
The chloroplast genome of P. vulgaris was reassembled by
GetOrganelle (Jin et al., 2020) based on the Illumina and
Nanopore sequencing data and then annotated by CPGAVAS2
(Shi et al., 2019). The assembled chloroplast genome size is 151, 346
bp (Figure S1). Identification of homologous fragments between
chloroplast genome and mitochondria genome of P. vulgaris using
the BLASTN online tool on the NCBI website (https://
www.ncbi.nlm.nih.gov/), with the default parameters. Results with
an identity value greater than 75 were retained (Table S1). The
results were visualized using the RCircos package (Zhang
et al., 2013).
2.6 Phylogenetic tree construction and
synteny analysis
A phylogenetic tree was constructed for 22 species (Table S2)
from 6 families of Lamiales based on the DNA sequences of 16
conserved mitochondrial PCGs (atp1, atp4, ccmB, ccmC, ccmFC,
ccmFN, cob, cox2, cox3, matR, nad1, nad2, nad3, nad5, nad6, rps13).
PhyloSuite (Zhang et al., 2020) and MAFFT(Katoh and Standley,
2013) were used to extract shared genes and align multiple
sequences. IQ-TREE (Nguyen et al., 2015) was used to build the
phylogenetic tree. ModelFinder (Kalyaanamoorthy et al., 2017;
Zhang et al., 2020) was used to find the most suitable model from
for out data based on Akaike information criterion (AIC). The
‘TVM+F+I+G4’model was finally chosen for maximum likelihood
tree construction. iTOL (https://itol.embl.de/)(Letunic and Bork,
2019) was used to visualize the results of phylogenetic analysis. The
mitochondrial genomes of seven Lamiaceae species (Scutellaria
barbata, Pogostemon heyneanus, Salvia miltiorrhiza, P. vulgaris,
Ajuga reptants, Rotheca serrata, and Vitex trifolia) were compared
using the BLAST program. Then homologous sequences longer
than 500 bp were retained as conserved collinearity blocks.
2.7 RNA editing event analysis methods
Prediction of RNA editing events was performed by the online
version of PREPACT3 (http://www.prepact.de/)(Lenz et al., 2018).
RNA editing sites of a total of 29 unique PCGs were predicted with a
cutoff value of 0.001.
3 Results
3.1 Genomic features of the P. vulgaris
mitochondrial genome
In this study, the P. vulgaris mitochondrial genome was
assembled. It is composed of two circular structures (Figure 1A).
We used Bandage (Wick et al., 2015) to visualize the mitochondrial
genome assembled based on Illumina data. Duplicated regions were
removed with the help of the third-generation sequencing reads.
Manual method was used to remove the nodes formed by nuclear
and chloroplast genes. The assembled raw mitochondrial genome
contains 47 nodes that including predicted duplication regions and
mitochondrial genomic regions migrating from chloroplast
(Figure 1B). After manually removing of redundant fragments,
two clear circular contigs were obtained (Figure 1C). The total
length of the assembled genome was 297, 777 bp and the GC
content was 43.92% (Table 1). The mitochondrial genome of P.
vulgaris was annotated with 29 unique PCGs (Figure 1A), 13 tRNA
genes and 3 rRNA genes (Table 2). The unique PCGs include five
ATP synthase genes (atp1, atp4, atp6, atp8 and atp9), nine NADH
dehydrogenase genes (nad1, nad2, nad3, nad4, nad4L, nad5, nad6,
nad7 and nad9), four ubiquinol cytochrome c reductase genes
(ccmB, ccmC, ccmFC and ccmFN), three cytochrome c oxidase
genes (cox1, cox2 and cox3), one transport membrane protein
gene (mttB), one maturases gene (matR), one cytochrome c
biogenesis gene (cob), one large subunit of ribosome gene (rpl16),
three small subunit of ribosome genes (rps3, rps12 and rps13), and
one succinate dehydrogenase gene (sdh4).
3.2 Codon usage analysis of PCGs
Codon preference analysis was performed on 29 unique PCGs
of P. vulgaris mitochondria. The codon usage by individual amino
acids is shown in Table S3. Relative synonymous codon usage
(RSCU) value greater than 1 indicated that the corresponding
amino acid was preferentially used. As shown in Figure 2, the
Methionine (Met) codon AUG and Tryptophan (Try) code UGG,
which both have the RSCU value of 1. There is also a general
preference for codon use in the PCGs of the mitochondria. For
example, Alanine (Ala) has a high preference for GCU with the
highest RSCU value of 1.61 among mitochondrial PCGs, followed
by Leucine (Leu) with a usage preference for UUA. Notably, the
Sun et al. 10.3389/fpls.2023.1237822
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maximum RSCU values of Lysine (Lys) and Phenylalanine (Phe)
were less than 1.2 and did not have a strong codon usage preference.
3.3 Repeated sequence analysis of the
mitochondrial genome of P. vulgaris
In MISA online prediction for the chromosome 1, a hit was
retained as a SSR when it met two criteria: the match score should
be greater than 69% and length should be between 10 and 33 bp. A
total of 47 SSRs were found on mitochondrial chromosome 1, with
monomeric and dimeric forms accounting for 31.91% of the total
SSRs. Adenine and thymine monomeric repeats accounted for
85.71% (6) of the 7 monomeric SSRs. There is a hexameric SSRs
in chromosome 1 (Figure 3A). Tandem repeats are widely found in
eukaryotic and prokaryotes genomes. Mitochondrial chromosome 1
contains 15 tandem repeats. Repetitive dispersed sequences in
mitochondrial chromosome 1 were examined. A total of 57 pairs
BC
A
FIGURE 1
The mitochondrial genome structure and annotation of P. vulgaris.(A) Annotations of P. vulgaris mitochondrial genome. (B) Two circular contigs of
P. vulgaris mitochondrial genome predicted by GetOrganelle. (C) The 2D structure of P. vulgaris mitochondrial genome after removing artificial
chloroplast and nuclear gene fragments. In B and C, the red nodes represent the predicted duplication regions and the green nodes represent the
predicted segments migrating to the mitochondrial genomes from chloroplast.
TABLE 1 Information on the mitochondrial genome of P. vulgaris.
Contigs Type Length GC content
Chromosome 1-2 Branched 297, 777 bp 43.92%
Chromosome 1 Circular 183, 505 bp 44.27%
Chromosome 2 Circular 114, 272 bp 43.36%
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of repetitive sequences with lengths greater than or equal to 30 bp
were observed (Figure 3B). Among them, 28 pairs of palindromic
repeats and 29 pairs of forward repeats were detected. The length of
the longest palindromic repeat was 1, 392 bp and that of the longest
forward repeat was 1, 429 bp.
In MISA online prediction for the chromosome 2, a hit was
retained as a SSR when it met two criteria: the match score should
be greater than 71% and length should be between 9 and 33 bp. A
total of 29 SSRs were found in mitochondrial chromosome 2, with
monomeric and dimeric forms accounting for 37.93% of total SSRs.
Adenine and thymine monomeric repeats accounted for 66.67% of
the three monomeric SSRs. Mitochondrial chromosome 2 contains
nine tandem repeats. A total of 30 pairs of repetitive sequences with
lengths greater than or equal to 30 bp were observed (Figure 3B).
Among them, 11 pairs of palindromic repeats and 19 pairs of
forward repeats were detected. The length of the longest
palindromic repeat was 54 bp and that of longest forward repeat
was 51 bp.
FIGURE 2
RSCU values of PCGs on P. vulgaris mitochondrial genome. The horizontal coordinate represents the 20 amino acids and the end codon. Vertical
coordinates indicate the frequency of use. Different codons of the same amino acid are colored differently.
TABLE 2 The encoding genes of P. vulgaris mitochondrial genome.
Group of genes Name of genes
ATP synthase atp1,atp4,atp6,atp8,atp9
NADH dehydrogenase nad1,nad2,nad3,nad4,nad4L,nad5,nad6,nad7,nad9
Cytochrome c biogenesis cob
Ubiquinol cytochrome c
reductase ccmB,ccmC,ccmFC,ccmFN
Cytochrome c oxidase cox1,cox2,cox3
Maturases matR
Transport membrane protein mttB
Large subunit of ribosome rpl16
Small subunit of ribosome rps3,rps12,rps13
Succinate dehydrogenase sdh4
Ribosome RNA rrn5,rrn18,rrn26
Transfer RNA trnC-GCA,trnD-GUC,trnE-UUC,trnfM-CAU,trnH-GUG,trnI-CAU,trnM-CAU,trnN-GUU,trnP-UGG,trnQ-UUG,trnS-GGA,trnW-
CCA,trnY-GUA
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3.4 DNA migration from chloroplast
to mitochondria
Based on the analysis of sequence similarity, a total of 36
fragments were homologous between the mitochondrial and
chloroplast genomes (Figure 4). The total length of these
homologous fragments was 28, 895 bp, accounting for 9.70% of
the total length of the mitochondrial genome. The longest
fragments were fragment 19 and fragment 20, both of which were
3, 276 bp (Table S1). By annotating these homologous sequences, 16
complete genes were identified on 36 homologous fragments (Table
S1), including 10 PCGs (ndhB, ndhI, psbJ, psbL, psbF, psbE, petL,
petG, rps4, and ycf15) and six tRNA genes (trnD-GUC, trnH-GUG,
trnM-CAU, trnP-UGG, trnS-GGA, and trnW-CCA).
3.5 Phylogenetic analysis and synteny
analysis based on mitochondrial
genomes of higher plants
A phylogenetic analysis was performed with 22 species based on
the DNA sequences of 16 conserved mitochondrial PCGs (atp1,
atp4, ccmB, ccmC, ccmFC, ccmFN, cob, cox2, cox3, matR, nad1,
nad2, nad3, nad5, nad6,andrps13).The two mitochondrial
genomes of Oleaceae were set as outgroups (Figure 5A). The
results showed that P. vulgaris belongs to the Lamiales family
Lamiaceae and is closely related to Salvia miltiorrhiza.The
topology of this mitochondrial DNA-based phylogeny is
consistent with the Angiosperm Phylogeny Group IV (Bennett
and Alarcon, 2015).
B
A
FIGURE 3
Horizontal coordinate indicates mitochondrial molecules and vertical coordinate indicates the number of repeat fragments. (A) Simple Sequence
Repeat of P. vulgaris mitochondrial genome. (B) Repeated sequence of P. vulgaris mitochondrial genome.
Sun et al. 10.3389/fpls.2023.1237822
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Alargenumberofhomologouscollinearity blocks were
detected in Lamiaceae species (Figure 5B). No collinearity blocks
with lengths less than 0.5 kb were retained. In addition, some
regions were unique to P. vulgaris, i.e., have no homologous region
with any other species. The collinearity blocks are not in the same
order. The mitochondrial genome sequences of these seven
Lamiaceae species are not sequentially conserved and have
undergone frequent genomic rearrangements.
3.6 The prediction of RNA editing events
A total of 379 potential RNA editing sites were identified on 29
mitochondrial PCGs (Figure 6), which are dominantly base C to U
editing (Table S1). Both ccmB and mttB had the highest number of
edits among all mitochondrial genes (35 RNA editing sites
identified), followed by ccmFN with 31 RNA editing events. In
addition, rpl16 and rps3 had the lowest number of edits among all
mitochondrial genes (one RNA editing sites identified).
4 Discussion
In general, plants contain three genomes, the nuclear genome, the
plastid genome and the mitochondrial genome. Recent advances in
plant whole genome study such as genome assembly or single cell
sequencing have greatly facilitated medicinal plant research; however,
plastid genome remains to be a powerful and cost-effective way(Guo
et al., 2022;Chen et al., 2023;Sun et al., 2023). The P. vulgaris
chloroplast genome has been sequenced (Han and Zheng, 2018), but
no mitochondrial sequencing has been completed for this species. In
this study, the P. vulgaris mitochondrial genome was assembled into
two circular structures with a total length of 297, 777 bp. Due to the
simplicity of codons,each amino acid corresponds to at least 1 codon,
and there are up to six corresponding codons. The codons of one
amino acid are often used at different frequencies. Codons may
correlate with gene expression levels (Trotta, 2013;Hia and Takeuchi,
2021). The use of genetic codons varies greatly from species to
species, which provides additional information on species-specific
evolution. Gene expression levels and gene length, tRNA abundance
and interactions, and codon position in the gene are some of the
factors that influence codon preference. There is a clear codon usage
preference in P. vulgaris mitochondria, with differences in the
frequency of different codons of each amino acid being used,
except for Met and Trp. For example, AAU and AAC are
synonymous codons of Asn, in which AAU was used 71% and
AAC was used 29%. Codon usage preference has been used to study
phylogeny and molecular evolution of genes among organisms. By
studying codon preference in Brassica campestris was found that
selection pressure plays most of the role in mutational pressure(Paul
et al., 2018;Parvathy et al., 2022). In addition, codon usage preference
should be considered when designing high yield and resistance genes.
Tandem repeat sequences are one of the most prevalent features
of genomic sequences. Tandem repeat sequences have important
FIGURE 4
The brown arc in the figure represents the mitochondrial genome, the green arc represents the chloroplast genome. The genome fragments
corresponding to the blue connecting lines between arcs are homologous fragments.
Sun et al. 10.3389/fpls.2023.1237822
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roles in biological evolution, gene regulation, gene expression, and
genome stability. A total of 58 SSRs were found in the mitochondria
of P. vulgaris, which provided great convenience for genetic studies
and species identification due to the maternal inheritance
characteristics of mitochondria. SSRs have been used to classify
different species, which is beneficial for species identification and
breeding of superior varieties. Among tandem repeats, SSR is a
special kind of tandem repeat sequence, which generally less than 6
bp. SSRs are often used for molecular marker of development due to
their characteristics such as dominant inheritance. They are
independent of the external environment and growth conditions
(Song et al., 2015). In addition, these markers have advantages such
as large numbers, stable traits, simple operation, and rapid
detection, and are widely used in the analysis and identification of
herbal plants (Chen et al., 2022). The mitochondrial genomes of
plants and animals have formed different evolutionary features.
In general, the mutation rate of plant mitochondrial genome is
lower than that of animal mitochondrial genome (Darracq et al.,
B
A
FIGURE 5
Evolution analysis of P. vulgaris.(A) The plants in the diagram belong to of Lamiales. Different families are represented by different colors, with P.
vulgaris represented in red. (B) Red-curved regions indicate where inversions occur, gray regions indicate regions of good homology, and white
regions indicate species-unique sequences.
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2011). Plant mitochondrial genome can integrate exogenous DNA
by migrating fragments with chloroplast genome (Law et al., 2022).
The presence of fragments of chloroplast genes was found in the
assembled mitochondrial genome of P. vulgaris. Mitochondrial and
chloroplast gene migration is an important mechanism for
biological evolution and diversity formation, which is important
for evolution, adaptation, and diversity of organisms (Xiong et al.,
2008). And this results in many structural variations in the plant
mitochondrial genome.
Phylogenetic relationships among species are the basis for many
biological studies. An accurate phylogenetic tree supports our
understanding of key transitions in evolution (Kapli et al., 2020).
Based on the phylogenetic tree constructed from 16 genes of
mitochondria, P. vulgaris was more closely related to Salvia
miltiorrhiza than other 20 species in this study. The tree matches the
latest classification of the Angiosperm Phylogeny Group IV (Bennett
and Alarcon, 2015). Collinearity research is a method to analyze the
relationship between homologous genes or sequences. The collinearity
of genes in plant genome usually decreases with the increase of
evolutionary distance (Wicker et al., 2010). A large number of
homologous collinearity blocks were detected in the P. vulgaris with
the rest of Lamiales species, but these collinearity blocks were short in
length.Inaddition,someblankregions were found. These sequences
areuniquetothespeciesandhavenohomologywiththerestofthe
species. The collinearity blocks were not in the same order among the
mitochondrial genomes of Lamiaceae. The results indicate that
the mitochondrial genome sequences of these seven Lamiaceae
species are not conservative in their alignments and undergo
frequent reorganization. RNA editing is the phenomenon of base
insertion, deletion, or conversionthatoccursinthecodingregionof
post-transcriptional RNA, such as 441 C-to-U editing sites have been
identified in Arabidopsis thaliana and 225 C-to-U editing sites in Salvia
miltiorrhiza. Due to the lack of suitable transcriptome data, P. vulgaris
was predicted through the website that it has 379 RNA editing sites, all
of which are C-to-U (Yang et al., 2022).
5 Conclusion
In this study, we have assembled the first complete
mitochondrial genome of P. vulgaris. It has a total length of 297,
777 bp, a GC content of 43.92%, and 29 unique PCGs. We found 76
SSRs in the mitochondrial genome. The phylogenetic analysis
showed that P. vulgaris is closely related to Salvia miltiorrhiza,
consistent with the Angiosperm Phylogeny Group IV. The
complete mitochondrial genome of P. vulgaris is useful to
understanding Lamiales evolution and could benefit following
works such as breeding of varieties of P. vulgaris.
Data availability statement
The original mitochondrial genome presented in the study are
publicly available. This data can be found in NCBI (https://
www.ncbi.nlm.nih.gov/) under the GenBank: OR113011.1
(https://www.ncbi.nlm.nih.gov/nuccore/OR113011.1/). The data
are publicly available. The datasets presented in this study can be
found in NCBI. The names of the repositories and accession
numbers can be found in the Supplementary Material.
Author contributions
CS conceived the study. YW and SZ collected the data. PF and
DG analyzed the data. ZS wrote the manuscript. All authors
contributed to the article and approved the submitted version.
FIGURE 6
Predicted RNA editing events in P. vulgaris mitochondrial genes. Horizontal coordinate indicates represents different genes and vertical coordinate
indicates the predicted number of RNA editing events.
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Funding
This work is supported by the Hubei science and technology
planning project (2020BCB038) and the talented person scientific
research start funds subsidization project of Chengdu University of
Traditional Chinese Medicine (030040015).
Conflict of interest
Author PF and DG are employed by Wuhan Benagen
Technology Co., Ltd.
The remaining authors declare that the research was conducted
in the absence of any commercial or financial relationships that
could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors
and do not necessarily represent those of their affiliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may be evaluated in this article, or
claim that may be made by its manufacturer, is not guaranteed or
endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online
at: https://www.frontiersin.org/articles/10.3389/fpls.2023.1237822/
full#supplementary-material
References
Allen, J. F. (2015). Why chloroplasts and mitochondria retain their own genomes
and genetic systems: Colocation for redox regulation of gene expression. Proc. Natl.
Acad. Sci. U.S.A. 112 (33), 10231–10238. doi: 10.1073/pnas.1500012112
Arseneau, J. R., Steeves, R., and Laflamme, M. (2017). Modified low-salt CTAB
extraction of high-quality DNA from contaminant-rich tissues. Mol. Ecol. Resour 17
(4), 686–693. doi: 10.1111/1755-0998.12616
Bai, Y., Xia, B., Xie, W., Zhou, Y., Xie, J., Li, H., et al. (2016). Phytochemistry and
pharmacological activities of the genus Prunella. Food Chem. 204, 483–496.
doi: 10.1016/j.foodchem.2016.02.047
Beier, S., Thiel, T., Münch, T., Scholz, U., and Mascher, M. (2017). MISA-web: a web
server for microsatellite prediction. Bioinformatics 33 (16), 2583–2585. doi: 10.1093/
bioinformatics/btx198
Bennett, B. C., and Alarcon, R. (2015). Hunting and hallucinogens: The use
psychoactive and other plants to improve the hunting ability of dogs. J.
Ethnopharmacol 171, 171–183. doi: 10.1016/j.jep.2015.05.035
Benson, G. (1999). Tandem repeats finder: a program to analyze DNA sequences.
Nucleic Acids Res. 27 (2), 573–580. doi: 10.1093/nar/27.2.573
Birky, C. W.Jr. (2001). The inheritance of genes in mitochondria and chloroplasts:
laws, mechanisms, and models. Annu. Rev. Genet. 35, 125–148. doi: 10.1146/
annurev.genet.35.102401.090231
Chen, H., Guo, M., Dong, S., Wu, X., Zhang, G., He, L., et al. (2023). A chromosome-
scale genome assembly of Artemisia argyi reveals unbiased subgenome evolution and
key contributions of gene duplication to volatile terpenoid diversity. Plant Commun. 4
(3), 100516. doi: 10.1016/j.xplc.2023.100516
Chen, S., Li, Z., Zhang, S., Zhou, Y., Xiao, X., Cui, P., et al. (2022). Emerging
biotechnology applications in natural product and synthetic pharmaceutical analyses.
Acta Pharm. Sin. B 12 (11), 4075–4097. doi: 10.1016/j.apsb.2022.08.025
Chen, Y., Ye, W., Zhang, Y., and Xu, Y. (2015). High speed BLASTN: an accelerated
MegaBLAST search tool. Nucleic Acids Res. 43 (16), 7762–7768. doi: 10.1093/nar/
gkv784
Cheng, Y., He, X., Priyadarshani, S., Wang, Y., Ye, L., Shi, C., et al. (2021). Assembly
and comparative analysis of the complete mitochondrial genome of Suaeda glauca.
BMC Genomics 22 (1), 167. doi: 10.1186/s12864-021-07490-9
Darracq, A., Varre,J.S.,Mare
chal-Drouard,L.,Courseaux,A.,Castric,V.,
Saumitou-Laprade, P., et al. (2011). Structural and content diversity of mitochondrial
genome in beet: a comparative genomic analysis. Genome Biol. Evol. 3, 723–736.
doi: 10.1093/gbe/evr042
Gualberto, J. M., Mileshina, D., Wallet, C., Niazi, A. K., Weber-Lotfi, F., and Dietrich,
A. (2014). The plant mitochondrial genome: dynamics and maintenance. Biochimie
100, 107–120. doi: 10.1016/j.biochi.2013.09.016
Guo, M., Pang, X., Xu, Y., Jiang, W., Liao, B., Yu, J., et al. (2022). Plastid genome data
provide new insights into the phylogeny and evolution of the genus Epimedium. J. Adv.
Res. 36, 175–185. doi: 10.1016/j.jare.2021.06.020
Han, Y. W., and Zheng, T. Y. (2018). The complete chloroplast genome of the
common self-heal, Prunella vulgaris (Lamiaceae). Mitochondrial DNA B Resour 3 (1),
125–126. doi: 10.1080/23802359.2018.1424587
Hia,F.,andTakeuchi,O.(2021).TheeffectsofcodonbiasandoptimalityonmRNAand
protein regulation. Cell Mol. Life Sci. 78 (5), 1909–1928. doi: 10.1007/s00018-020-03685-7
Jackman, S. D., Coombe, L., Warren, R. L., Kirk, H., Trinh, E., MacLeod, T., et al.
(2020). Complete Mitochondrial Genome of a Gymnosperm, Sitka Spruce (Picea
sitchensis), Indicates a Complex Physical Structure. Genome Biol. Evol. 12 (7), 1174–
1179. doi: 10.1093/gbe/evaa108
Jin, J. J., Yu, W. B., Yang, J. B., Song, Y., dePamphilis, C. W., Yi, T. S., et al. (2020).
GetOrganelle: a fast and versatile toolkit for accurate de novo assembly of organelle
genomes. Genome Biol. 21 (1), 241. doi: 10.1186/s13059-020-02154-5
Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., von Haeseler, A., and Jermiin, L.
S. (2017). ModelFinder: fast model selection for accurate phylogenetic estimates. Nat.
Methods 14 (6), 587–589. doi: 10.1038/nmeth.4285
Kapli, P., Yang, Z., and Telford, M. J. (2020). Phylogenetic tree building in the
genomic age. Nat. Rev. Genet. 21 (7), 428–444. doi: 10.1038/s41576-020-0233-0
Katoh, K., and Standley, D. M. (2013). MAFFT multiple sequence alignment
software version 7: improvements in performance and usability. Mol. Biol. Evol. 30
(4), 772–780. doi: 10.1093/molbev/mst010
Kurtz, S., Choudhuri, J. V., Ohlebusch, E., Schleiermacher, C., Stoye, J., and
Giegerich, R. (2001). REPuter: the manifold applications of repeat analysis on a
genomic scale. Nucleic Acids Res. 29 (22), 4633–4642. doi: 10.1093/nar/29.22.4633
Law, S. S. Y., Liou, G., Nagai, Y., Gimenez-Dejoz, J., Tateishi, A., Tsuchiya, K., et al.
(2022). Polymer-coated carbon nanotube hybrids with functional peptides for gene
delivery into plant mitochondria. Nat. Commun. 13 (1)2417. doi: 10.1038/s41467-022-
30185-y
Lenz, H., Hein, A., and Knoop, V. (2018). Plant organelle RNA editing and its
specificity factors: enhancements of analyses and new database features in PREPACT
3.0. BMC Bioinf. 19 (1), 255. doi: 10.1186/s12859-018-2244-9
Letunic, I., and Bork, P. (2019). Interactive Tree Of Life (iTOL) v4: recent updates
and new developments. Nucleic Acids Res. 47 (W1), W256–w259. doi: 10.1093/nar/
gkz239
Lewis, S. E., Searle, S. M., Harris, N., Gibson, M., Lyer, V., Richter, J., et al. (2002).
Apollo: a sequence annotation editor. Genome Biol. 3 (12), Research0082. doi: 10.1186/
gb-2002-3-12-research0082
Li, H., and Durbin, R. (2009). Fast and accurate short read alignment with Burrows-
Wheeler transform. Bioinformatics 25 (14), 1754–1760. doi: 10.1093/bioinformatics/
btp324
Li, C., Huang, Q., Fu, X., Yue, X. J., Liu, R. H., and You, L. J. (2015).Characterization,
antioxidan t and immunomodulatory activities of polysaccharides from Prunell a
vulgaris Linn. Int. J. Biol. Macromol 75, 298–305. doi: 10.1016/j.ijbiomac.2015.01.010
Liu,Z.,Dong,F.,Wang,X.,Wang,T.,Su,R.,Hong,D.,etal.(2017).A
pentatricopeptide repeat protein restores nap cytoplasmic male sterility in Brassica
napus. J. Exp. Bot. 68 (15), 4115–4123. doi: 10.1093/jxb/erx239
Liu, Z., Hua, Y., Wang, S., Liu, X., Zou, L., Chen, C., et al. (2020). Analysis of the
Prunellae Spica transcriptome under salt stress. Plant Physiol. Biochem. 156, 314–322.
doi: 10.1016/j.plaphy.2020.09.023
Lowe, T. M., and Eddy, S. R. (1997). tRNAscan-SE: a program for improved
detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 25 (5),
955–964. doi: 10.1093/nar/25.5.955
Mackenzie, S., and McIntosh, L. (1999). Higher plant mitochondria. Plant Cell 11
(4), 571–586. doi: 10.1105/tpc.11.4.571
Sun et al. 10.3389/fpls.2023.1237822
Frontiers in Plant Science frontiersin.org10
Nguyen, L. T., Schmidt, H. A., von Haeseler, A., and Minh, B. Q. (2015). IQ-TREE: a
fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies.
Mol. Biol. Evol. 32 (1), 268–274. doi: 10.1093/molbev/msu300
Nielsen, B. L., Cupp, J. D., and Brammer, J. (2010). Mechanisms for maintenance,
replication, and repair of the chloroplast genome in plants. J. Exp. Bot. 61 (10), 2535–
2537. doi: 10.1093/jxb/erq163
Parvathy, S. T., Udayasuriyan, V., and Bhadana, V. (2022). Codon usage bias. Mol.
Biol. Rep. 49 (1), 539–565. doi: 10.1007/s11033-021-06749-4
Paul, P., Malakar, A. K., and Chakraborty, S. (2018). Compositional bias coupled
with selection and mutation pressure drives codon usage in Brassica campestris genes.
Food Sci. Biotechnol. 27 (3), 725–733. doi: 10.1007/s10068-017-0285-x
Richardson, A. O., Rice, D. W., Young, G. J., Alverson, A. J., and Palmer, J. D. (2013).
The "fossilized" mitochondrial genome of Liriodendron tulipifera: ancestral gene
content and order, ancestral editing sites, and extraordinarily low mutation rate.
BMC Biol. 11, 29. doi: 10.1186/1741-7007-11-29
Shao, D., Ma, Y., Li, X., Ga, S., and Ren, Y. (2021). The sequence structure and
phylogenetic analysis by complete mitochondrial genome of kohlrabi (Brassica oleracea
var. gongylodes L.). Mitochondrial DNA B Resour 6 (9), 2714–2716. doi: 10.1080/
23802359.2021.1966341
Shi, L., Chen, H., Jiang, M., Wang, L., Wu, X., Huang, L., et al. (2019). CPGAVAS2,
an integrated plastome sequence annotator and analyzer. Nucleic Acids Res. 47 (W1),
W65–w73. doi: 10.1093/nar/gkz345
Silvestris, D. A., Scopa, C., Hanchi, S., Locatelli, F., and Gallo, A. (2020). De Novo A-to-I
RNA Editing Discovery in lncRNA. Cancers (Basel) 12 (10). doi: 10.3390/cancers12102959
Sloan, D. B., Wu, Z., and Sharbrough, J. (2018). Correction of Persistent Errors in
Arabidopsis Reference Mitochondrial Genomes. Plant Cell 30 (3), 525–527.
doi: 10.1105/tpc.18.00024
Song, X., Ge, T., Li, Y., and Hou, X. (2015). Genome-wide identification of SSR and
SNP markers from the non-heading Chinese cabbage for comparative genomic
analyses. BMC Genomics 16 (1), 328. doi: 10.1186/s12864-015-1534-0
Su, X., Yang, L., Wang, D., Shu, Z., Yang, Y., Chen, S., et al. (2022). 1 K Medicinal
Plant Genome Database: an integrated database combining genomes and metabolites of
medicinal plants. Hortic. Res. 9, uhac075. doi: 10.1093/hr/uhac075
Sun, S., Shen, X., Li, Y., Li, Y., Wang, S., Li, R., et al. (2023). Single-cell RNA
sequencing provides a high-resolution roadmap for understanding the multicellular
compartmentation of specialized metabolism. Nat. Plants 9 (1), 179–190. doi: 10.1038/
s41477-022-01291-y
Tillich, M., Lehwark, P., Pellizzer, T., Ulbricht-Jones, E. S., Fischer, A., Bock, R., et al.
(2017). GeSeq - versatile and accurate annotation of organelle genomes. Nucleic Acids
Res. 45 (W1), W6–w11. doi: 10.1093/nar/gkx391
Trotta, E. (2013). Selection on codon bias in yeast: a transcriptional hypothesis.
Nucleic Acids Res. 41 (20), 9382–9395. doi: 10.1093/nar/gkt740
Turmel, M., Otis, C., and Lemieux, C. (2016). Mitochondrion-to-Chloroplast DNA
Transfers and Intragenomic Proliferation of Chloroplast Group II Introns in
Gloeotilopsis Green Algae (Ulotrichales, Ulvophyceae). Genome Biol. Evol. 8 (9),
2789–2805. doi: 10.1093/gbe/evw190
Wang, S., Li, D., Yao, X., Song, Q., Wang, Z., Zhang, Q., et al. (2019). Evolution and
Diversification of Kiwifruit Mitogenomes through Extensive Whole-Genome
Rearrangement and Mosaic Loss of In tergenic Sequences in a Highly Variable
Region. Genome Biol. Evol. 11 (4), 1192–1206. doi: 10.1093/gbe/evz063
Wick, R. R., Schultz, M. B., Zobel, J., and Holt, K. E. (2015). Bandage: interactive
visualization of de novo genome assemblies. Bioinformatics 31 (20), 3350–3352.
doi: 10.1093/bioinformatics/btv383
Wicker, T., Buchmann, J. P., and Keller, B. (2010). Patching gaps in plant genomes
results in gene movement and erosion of colinearity. Genome Res. 20 (9), 1229–1237.
doi: 10.1101/gr.107284.110
Xiong, A. S., Peng, R. H., Zhuang, J., Gao, F., Zhu, B., Fu, X. Y., et al. (2008). Gene
duplication and transfer events in plant mitochondria genome. Biochem. Biophys. Res.
Commun. 376 (1), 1–4. doi: 10.1016/j.bbrc.2008.08.116
Yang, H., Chen, H., Ni, Y., Li, J., Cai, Y., Ma, B., et al. (2022). De Novo Hybrid
Assembly of the Salvia miltiorrhiza Mitochondrial Genome Provides the First Evidence
of the Multi-Chromosomal Mitochondrial DNA Structure of Salvia Species. Int. J. Mol.
Sci. 23 (22). doi: 10.3390/ijms232214267
Zhang, D., Gao, F., Jakovlic, I., Zou, H., Zhang, J., Li, W. X., et al. (2020). PhyloSuite:
An integrated and scalable desktop platform for streamlined molecular sequence data
management and evolutionary phylogenetics studies. Mol. Ecol. Resour 20 (1), 348–355.
doi: 10.1111/1755-0998.13096
Zhang, H., Meltzer, P., and Davis, S. (2013). RCircos: an R package for Circos 2D
track plots. BMC Bioinf. 14, 244. doi: 10.1186/1471-2105-14-244
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