Seven mitochondrial genomes of tribe Hylurgini

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1. Background

Bark and ambrosia beetles comprise the subfamilies Scolytinae and Platypodinae in the family Curculionidae [1–7]. Hylurgini (Coleoptera: Curculionidae: Scolytinae), is a large group of Scolytinae which contains 14 genera: Chaetoptelius Fuchs, Dendroctonus Erichson, Dendrotrupes Broun, Hylurdrectonus Schedl, Hylurgonotus Schedl, Hylurgopinus Swaine, Hylurgus Latreille, Pachycotes Sharp, Pseudohylesinus Swaine, Pseudoxylechinus Wood & Huang, Sinophloeus Brèthes, Tomicus Latreille, Xylechinosomus Schedl, and Xylechinus Chapuis [4, 5, 8–12]. There are three genera in the tribe Hylurgini occurring in China, i.e., Tomicus, Dendroctonus and Hylurgus.

Many investigations have identified two or more species within the tribe Hylurgini that cooperatively damage their hosts in the same location. In some areas, the simultaneous species of Hylurgini are all native and belong to the same genus. For example, in 1997, a survey was conducted in Kunming City and Shuangbai County, Chuxiong City, Yunnan Province. Tomicus minor (Hartig) and T. yunnanensis concurrently inflicted damage on Pinus yunnanensis, leading to tree vulnerability and expedited mortality [13–15]. In 2011, Tomicus. brevipilosus, T. minor and T. yunnanensis were reported to co-occur in Qujing County, Jianshui City and Chuxiong City of Yunnan Province [16, 17]. In Arizona, USA, Dendroctonus frontalis Zimm. and Dendroctonus brevicomis LeConte were found on the same tree [18, 19]. In some areas, the invasive species of Hylurgini became co-damaging with indigenous species. T. piniperda and H. ligniperda were found to damage the host together in the Muping District of Yantai City, Shandong Province. This phenomenon was also observed in Dendroctonus valens and T. piniperda at Heilihe National Nature Reserve, Inner Mongolia.

There are many important forest pests in the tribe Hylurgini. Some species could cause massive damage during outbreaks. For example, Dendroctonus ponderosae Hopkin, a native species of western North America, caused massive forestry damage to more than 1.2 million hectares in 2004 [20]. D. valens and H. ligniperda, have been introduced from their indigenous habitats and have become significant invasive species, both caused significant destruction to forests following their introduction to China [7, 21–23]. Since its initial identification in 2020, H. ligniperda has inflicted significant damage on Pinus thunbergii inside the coastal shelter belt of Moping District, Yantai City, Shandong Province. [24]. The invasive D. valens was introduced into China in 1998, mainly damaging healthy Pinus tabuliformis with a diameter at breast height greater than 10 cm or more than 30 years old [25, 26]. Tomicus spp., found in many regions of China, damage pine trees by feeding on the shoot and trunk [27]. Since the 1980s, in Yunnan Province alone, the damaged area has reached more than 10 × 10⁴ hm² all year round [28].

In the study by Johnson et al. [29], 251 protein-coding genes from the subfamily Scolytinae were analyzed to establish the phylogenetic relationships of the subfamily Scolytinae, which consists of 22 tribes, including two species of Dendroctonus in the tribe Hylurgini. However, in morphological classification, the tribes of Xyleborini, Corthylini and Cryphalini are monophyletic [29–32]. According to the findings of Johnson et al., Xyleborini is associated with Dryocoetini, Corthylini is polyphyletic, and Cryphalini is significantly polyphyletic [29]. The phylogenetic relationships of this subfamily are still confusing due to the conflicting phylogenetic frameworks mentioned above, and data on Hylurgini are lacking, so further clarification is needed.

At present, mitochondrial genomes have been used in a wide range of studies such as species identification, molecular evolution and molecular markers for comparative genomics, and are of great significance in population genetics and evolution [26, 33–39]. Insect mitochondrial genome is more easily amplified than the nuclear genome, lacking non-coding regions (i.e., introns), maternal inheritance, low recombination rate, small size, rapid mutation rate, and so on [40–42]. Currently, the mitochondrial genomes of Coleoptera have been released in GenBank with 572 species, and 39 species of Scolytinae have complete mitochondrial genome data [43, 44]. Three species of Hylurgini have complete mitochondrial genomes, including D. valens, D. rufipennis and H. ligniperda [45]. The studies on Hylurgini were mainly focused on morphology and molecular identification based on the cytochrome c oxidase subunit I (COI) gene [46]. However, morphological characteristics are ineffective in solving intergeneric and interspecific phylogenetic relationships [16, 47–50]. The mitochondrial gene data of Hylurgini in GeneBank was seriously lacking except for the cytochrome oxidase I (COI) gene, which hindered the development of phylogenetic studies on it.

Here, we sequenced, assembled, and annotated the mitochondrial genomes of seven Hylurgini species, including D. valens, H. ligniperda, H. micklitzi, T. piniperda, T. brevipilosus, T. minor, T. yunnanensis and H. micklitzi. They have caused severe damage in China except for H. micklitzi. H. micklitzi currently does not distribute in China, but has extensive distribution in Europe. The mitochondrial genomes of seven Hylurgini species were compared and analyzed to understand their structure and base composition and to clarify the phylogenetic relationship between the tribe Hylurgini and other sister groups in Scolytinae. Phylogenetic studies of the tribe Hylurgini can provide us with a possible evolutionary framework to clarify the phylogenetic relationships of these species. Understanding phylogenetic relationships can also further advance knowledge of their niche changes and common hazards. Moreover, the members of the tribe Hylurgini are generally small in size, with close morphology of sympatric species. Its identification relies on taxonomists and strict identification conditions. Sequencing the mitochondrial genome could also advance the development of molecular markers for the tribe Hylurgini. Our results have important implications for studying mitochondrial genomes and clarifying the phylogenetic relationship.

2. Materials and methods

2.1 Sampling and genomic DNA extraction

Samples of seven species of bark beetle adults were collected from China and France. From October 16^th to 23^th, 2021. More than 600 individuals of T. yunnanensis, T. minor, T. brevipilosus were collected from three sites in Yunnan Province. D. valens was collected in Heilihe National Nature Reserve, Inner Mongolia. H. ligniperda and T. piniperda were collected from Muping, Shandong Province. H. micklitzi has been collected by the Orléans Forest Zoology Research unit (French Institute for Agri-Food and Environmental Research- INRAE), at Le Thoronet, Southern France by attractive traps on July 15^th 2021 (Table 1). The above specimens were stored in the laboratory (College of Forestry, Beijing Forestry University) refrigerator in absolute ethyl alcohol at −20°C. A Zeiss AxioZoom V16 type microscope was used to observe and take photos of the samples (Figs 1 and 2). We identified the specimens with reference to these previous studies [9, 16, 49, 51]. According to the instructions, the AxyPrep Multisource Genomic DNA Miniprep Kit (Axygen, USA) was used to extract the genomic DNA from the entire body of specimens from the same locality of each Hylurgini species. The total DNA quality was examined with 1% agarose gel, and the concentration was measured with a NanoDrop 2000 spectrophotometer (Thermo Scientific, USA).

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a. Adult dorsal view of Tomicus brevipilosus, b. Eytral declivity of Tomicus brevipilosus, c. Adult dorsal view of Tomicus minor, d. Eytral declivity of Tomicus minor, e. Adult dorsal view of Tomicus piniperda, f. Eytral declivity of Tomicus piniperda, g. Adult dorsal view of Tomicus yunnanensis. h. Eytral declivity of Tomicus yunnanensis.

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i. Adult dorsal view of Hylurgus ligniperda, j. Eytral declivity of Hylurgus ligniperda, k. Adult dorsal view of Hylurgus micklitzi, l. Eytral declivity of Hylurgus micklitzi, m. Adult dorsal view of Dendroctonus valens, n. Eytral declivity of Dendroctonus valens.

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2.2 Mitochondrial genome sequencing and assembly

Samples with qualified mass and concentration greater than 2 ng/μl were sent to Shanghai Majorbio Bio-pharm Technology Co., Ltd for high-throughput sequencing. The library was constructed and sequenced using the Illumina HiSeq X platform based on Sequencing by Synthesis (SBS) technique. Filter the raw data using Hylastes attenuatus (KX035212.1) as the reference sequence. Clean reads were assembled with the software GetOrganelle (https://github.com/Kinggerm/GetOrganelle) [52] under the K-mer = 21, 45, 65, 85, 105. To ensure the accuracy of the results, NOVOPlasty4.2 (https://github.com/ndierckx/NOVOPlasty) [53] was also used with Hylastes attenuatus (KX035212.1) as a seed sequence for mitochondrial genome assembly under K-mer = 33. Then the results of the two software were compared, and the full length of mitochondrial genome sequences of the seven species were obtained.

2.3. Mitochondrial genome annotation and analysis

MITOS (http://mitos2.bioinf.uni-leipzig.de/index.py) [54] was used to annotate the mitochondrial genome results of seven species. The type of reference gene set was Metazoa, and the Genetic Code was Invertebrate. The BLAST function of NCBI was used to confirm the accuracy of the annotation results. Based on the available mitochondrial genome data of the family Scolytinae, the start codons and stop codons with problems in 13 PCGs were manually adjusted. ARWEN (www.acgt.se/online.html) [55] and tRNAscan—SE 2.0 (http://trna.ucsc.edu/tRNAscan-SE/) were used to predict the secondary structure of tRNA and annotate the undiscovered tRNA [56]. Using the Tandem Repeats the Finder online server (http://tandem.bu.edu/trf/trf.html) to find concatenation repeats sequences [57]. The two rRNA genes were compared with Dendroctonus rufipennis, Hylastes attenuates Erichson and Polygraphus poligraphus (Linnaeus) of the subfamily Scolytinae, and manually adjusted by them. MEGA11 [58] was used to analyse the nucleotide codon usage frequency (RSCU) and nucleic acid composition. According to the formula, the AT-skew = [(A − T)/(A + T)] and GC-skew = [(G − C)/(G + C)] calculating nucleotide differences (AT deflection and GC deflection). The synonymous substitution rate (dS) and non-synonymous substitution rate (dN) were calculated by PALM 4.9j [59]. The heatmap was plotted using TBtools (Toolbox for biologists) [60]. Finally, CGView Server (http://stothard.afns.ualberta.ca/cgview_server) [61] was used to draw the mitochondrial genome maps.

2.4 Sequence alignment and phylogenetic analysis

Complete published mitochondrial genome sequences of 29 species from 10 tribes of Scolytinae were downloaded from the GenBank (S1 Table), and 13 protein-coding genes (PCGs) were extracted using the Phylosuite1.2.2 [62] software. MAFFT [63] was used to conduct multiple sequence alignment. Then, the sequences were concatenated to obtain a nucleotide sequence data set of protein-coding genes. The sequence of Acrida cinerea (NC_014887.1) was selected as an outgroup. We used IQ-TREE (maximum likelihood, ML) [64] and MrBayes 3.2.6 (Bayesian inference, BI) [65] of Phylosuite1.2.2 software to construct phylogenetic trees. In IQ-TREE, we selected the “Auto” model. The confidence level of the branch node was estimated using the 1,000 ultrafast bootstrap replicates. With the help of ModelFinder [66], the optimal nucleotide substitution model was selected as GTR + I + G + F, and MrBayes performed Bayesian inference under the GTR + I + G + F model, operating for 2,000,000 generations with two simultaneous runs, sampling once every 1,000 generations, and the burn-in fraction was set to 0.25. The value of the average standard deviation of split frequencies was less than 0.01, and there was little difference between the results of the two runs, and the parameters converged [67]. The tree files were visualized by iTOL (Interactive Tree Of Life) (http://itol.embl.de) [68]. Finally, MEGA11 software was used to calculate the genetic distance of Hylurgini.

3. Results

3.1 Mitochondrial genome structure and base composition of seven Hylurgini species

The mitochondrial genome sequences of seven Hylurgini species ranged from 15,339 bp to 17,545 bp. The shortest was T. piniperda and the longest was T. minor. T. minor, T. yunnanensis, and D. valens were composed of a control region and 37 genes (13 protein-coding genes, 22 tRNA genes and two rRNA genes). The other four species, T. brevipilosus, T. piniperda, H. ligniperda and H. micklitzi, were missing tRNA^Ile genes, all of which were 36 genes (Figs 3 and 4). Among the seven newly sequenced mitochondrial genomes, nine protein-coding genes (ND2, COI, COII, ATP8, ATP6, COIII, ND3, ND6, Cytb), 14 tRNA genes (tRNA^Ile, tRNA^Met, tRNA^Trp, tRNA^Leu(UUR), tRNA^Lys, tRNA^Asp, tRNA^Gly, tRNA^Ala, tRNA^Arg, tRNA^Asn, tRNA^Ser(AGN), tRNA^Glu, tRNA^Thr, tRNA^Ser(UCN)) were distributed on the J strand (majority strand, encodes more genes in the DNA double strand), while the remaining 14 genes were on the N strand (minority strand, encodes a relatively small number of genes in the DNA double strand) [69, 70].

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There were 13 non-coding regions in D. valens, 13 in H. ligniperda and H. micklitzi, 16 in T. minor, T. brevipilosus and T. piniperda, and 17 in T. yunnanensis at most. Except for the control region, the most extended non-coding region was in tRNA^Ile-tRNA^Gln of T. yunnanensis, with a length of 281 bp. The overlap of the seven Hylurgini species varied from 8 to 14 places. Two overlapping regions, tRNA^Lys-tRNA^Asp and ATP8-ATP6, were found in all seven bark beetle species.

The content of A+T in the whole mitochondrial genome of the seven Hylurgini species ranged from 73.24% to 78.81%, with the lowest content of D. valens and the highest content of H. micklitzi, showing an obvious AT bias. The AT-skew of the seven species was 0.024 to 0.080, and the GC-skew was negative, ranging from −0.239 to −0.158.

3.2 Mitochondrial protein-coding genes and relative synonymous codon usage

In seven mitochondrial genomes, the total length of 13 protein-coding genes ranged from 11,082 bp to 11,138 bp, accounting for 61.84% to 72.61% of the total sequence, in which ND5 of T. brevipilosus was the longest, 1,723 bp. ATP8 of H. micklitzi, D. valens, and H. ligniperda was the shortest, 156 bp. Most PCGs were started by the insect standard start codon ATN. However, the start codon of T. minor’s COI gene was TCG; the start codon of the protein-coding gene ND1 of T. yunnanensis, T. brevipilosus, H. micklitzi and T. piniperda was TTG respectively. As for stop codon, five PCGs (ND2, COI, ATP6, COIII, ND6) ended with TAA in seven mitochondrial genomes sequenced in this study. Cytb of T. brevipilosus and H. micklitzi, ND4L of H. ligniperda, ND1 of T. yunnanensis and D. valens, ND3 of H. micklitzi, D. valens and T. minor all had TAG as the stop codon. ND5 of H. ligniperda was terminated by TA residue. In contrast, the remaining PCGs including COII, ND5, ND4 and ND1 appeared to terminate with a T residue in seven species. For example, ND5, ND4 and ND1 of H. micklitzi, ND5, ND4 of D. valens.

The AT content of PCGs was 71.6% to 77.9%. Contents of the third codon position AT H. micklitzi, H. ligniperda, T. minor, T. yunnanensis and T. piniperda (77.4% to 81.8%) were higher than those of the first (70% to 77.5%) and the second (69.5% to 78.3%) codon positions. In contrast, D. valens and T. brevipilosus had higher AT content at the first codon position (73% and 79.2%) than at the second (71.3% and 72.3%) and third (70.6% and 77.2%) codon positions. The AT-skew range of PCGs for the seven species was −0.152 to −0.129, and the range of GC-skew was −0.067 to −0.008.

In addition, the relative synonymous codon usage (RSCU) analysis results showed that in the mitochondrial genome PCGs of seven Hylurgini species, there were 22 codon families containing 62 codons (excluding two stop codons). The codon families encoding amino acids Ala, Arg, Gly, Pro, Ser2, Thr, and Val are frequently used in all seven mitochondrial genomes (Fig 5). Among the seven mitochondrial genomes, UUU (Phe), UUA (Leu), CCU (Pro), GUU (Val), GCU (Ala), CGA (Arg), ACU (Thr), GGA (Gly) were the most frequently used. The five most frequent codons make up 10.94% to 15.16% of all PCG codons. The least frequently used codon was the CCG (Pro) codon of T. yunnanensis, with an RSCU of 0.07.

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Compared with other synonymous codons, A or T ranked third in the double and quadruple degenerate synonymous codons were overused. In this study, there was a preference for codons, except CCU (Pro) (1.14), AGG (Ser1) (1.15), and GGG (Gly) (1.06), all of which ended in A or T (U). This suggests that, in addition to the effect of selection on the bias of codon usage, the mutation pressure at the third codon position from GC to AT is higher than in the opposite direction (AT to GC), as well as at the first and second codon positions [71]. In addition, the five most frequently used codons in each of the seven mitochondrial genomes were not identical. For example, the five codons with the highest frequency (maximum RSCU value) of D. valens and H. ligniperda were UUA(Leu), CCU(Pro), UCU(Ser2), GUU(Val), and GCU(Ala), that of H. micklitzi and T. brevipilosus were UUA (Leu), CCU (Pro), CGA (Arg), ACU (Thr) and GCU (Ala), and that of T. minor were UUA (Leu), CCU (Pro), UCU (Ser2), CGA (Arg) and ACU(Thr). It could be seen that different species of the same family may have different preferences for using synonymous codons. However, the specific situation needs further analysis.

3.3 Synonymous substitution rate and the non-synonymous substitution rate of mitochondrial protein-coding genes

To determine the molecular sequence evolution mechanism of Hylurgini, we also analysed the Synonymous substitution rate (dS) and the Non-synonymous substitution rate (dN) of each PCGs (Fig 6). The results showed that all PCGs of seven mitochondrial genomes evolved under purification selection (dN/dS < 1). On the one hand, the dN/dS values of all PCGs were very low, ranging from 0.0021 to 0.4001, indicating strong purification selection. The ATP8 (dN/dS = 0.3703) of H. micklitzi vs. D. valens and the ATP8 (dN/dS = 0.4001) of H. ligniperda vs. D. valens were closer to 1, indicating that the purification selection of this gene was looser. In the Hylurgini, the purified selected genes were sorted by decreasing selection intensity (increasing dN/dS value) as follows: COI > COII > Cytb> COIII > ATP6 > ND5 > ND1 > ND3 > ND4 > ND4L > ND2 > ND6 > ATP8. None of the PCGs had dN/dS > 1, indicating that Hylurgini PCGs were mainly influenced by purification selection in the evolutionary process, while ATP8 encountered relatively small purification selection pressure. HeatMap shows that ND2, ND4L and ND6 were under loose purification selection except for ATP8 (Fig 7). While CO genes (COI, COII and COIII) were under relatively strong purification selection pressure. In conclusion, purification selection would eliminate harmful mutations in the population, and all PCGs of the Hylurgini can be used for our phylogenetic analysis.

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3.4 Transfer and ribosomal RNA genes of mitogenome

A total of 22 tRNA genes were annotated by MITOS2. The length of tRNA genes ranged from 60 bp (tRNA^Cys of D. valens) to 71 bp (tRNA^Lys of D. valens, H. micklitzi, T. minor, T. brevipilosus, T. yunnanensis and T. piniperda). The average length of t-RNA is 64 bp. The secondary structure of 21 tRNA genes was typical of the cloverleaf, and only the tRNA^SER(AGN) was atypical in all seven Hylurgini, lacking a dihydrouracil (DHU) arm (Fig 8).

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Conserved sites and mutation sites were indicated in blue and red, respectively, and mismatched base pairs were marked with red solid dots.

In addition, the secondary structure prediction results showed that unmatched base pairs occurred on the stem of some tRNA genes. The mismatched pairs of G-U occurred on 11 tRNA genes, a total of 84 pairs. H. ligniperda had the most mismatches and T. brevipilosus had the least. The G-U mismatched pairs of tRNA^Ala, tRNA^Phe, tRNA^His, tRNA^Leu(CUN), and tRNA^Val occurred on acceptor stems. The mismatch pairs of tRNA^Gln, tRNA^Tyr, tRNA^Phe and tRNA^Pro occurred on DHU arm, tRNA^Ile on the anticodon arm, and tRNA^Trp, tRNA^Ser(AGN) occurred on TΨC stem (Fig 8).

The two rRNA, srRNA and lrRNA genes, were on the N-strand. The length of the lrRNA ranged from 1,283 bp to 1,301 bp. The shortest was H. micklitzi and the longest was T. yunnanensis. The length of srRNA ranged from 765 bp to 782 bp. The shortest was H. micklitzi and the longest was T. minor. The AT content of lrRNA ranged from 80.6% to 82.5%, which was higher than that of srRNA (79.3% to 80.6%). All of them had high A + T preference.

3.5 Phylogenetic analysis

We performed a phylogenetic analysis of 13 PCGs from 37 mitochondrial genomes (from 11 tribes of the subfamily Scolytinae). The same topologies were presented by constructing phylogenetic trees from two methods, likelihood (ML) and Bayesian inference (BI) (Figs 9 and 10). In the Bayesian inference, the tribe of Scolytini, Hylastini, Hylurgini, Xyloterini, Ipini, Xyleborini and Corthylini showed high bootstrap values. In the likelihood analysis, the tribe of Scolytini, Hylastini, Xyloterini, Ipini, Corthylini and Hylurgini showed high bootstrap values. These results allowed better support for the monophyly of the tribe and genera of our studied species. The results of the two methods showed consistent phylogenetic relationships. Scolytini was the first to separate from the other groups and clustered as a monophyletic branch. Phloeosinus perlatus of the tribe Phloeosinini and Polygraphus poligraphus of the tribe Polygraphini clustered as a monophyletic branch. The Hylastini and Hylurgini are monophyletic. Cryphalini and Xyloterini clustered into a monophyletic clade. Ipini with Dryocoetini, and Xyleborini formed a monophyletic lineage with Ipini sister to Dryocoetini and Xyleborini. Gnathotrichus materiarius and Pityophthorus pubescens of the tribe Corthylini formed a monophyletic branch. These results were consistent with morphological and single gene/multiple genes of the mitochondrial genomic PCGs tree [72].

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The numbers at nodes indicate Bayesian posterior probabilities.

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The numbers at nodes indicate ML bootstrap support values.

4. Discussion

4.1 Mitochondrial genomes comparison between Hylurgini and the other tribes of Scolytinae

The seven mitochondrial genomes newly sequenced were shorter than those of their sister groups published to NCBI (S2 Table). The mitochondrial genome structure of the seven bark beetles, as determined through our assembly and annotation, was congruent with previously known species of the tribes Phloeosinini and Ipini [72]. The mitochondrial genome structure was identical to that of ancestry insects [33]. All 22 tRNA genes of T. minor, T. yunnanensis and D. valens, were successfully annotated by MITOS2. However, tRNA^Ile of T. brevipilosus, T. piniperda, H. ligniperda and H. micklitzi were not annotated. The proximity of tRNA^Ile to the regulatory region and its abundance of A and T bases restricts Illumina sequencing runs, resulting in the detection of only 36 genes without comprehensive sequencing. The content of A + T of Hylurgini ranged from 73.24% to 78.81%, the content of D. valens was the lowest, and H. micklitzi was the highest, showing an obvious AT bias. In general, the species of Hylurgini had a low content of A + T compared with other species of Scolytinae (S2 Table). The AT-skew of the whole mitochondrial genome of the seven species was positive, indicating that there were more bases A than C. The GC-skew was negative, indicating that the content of G in the mitochondrial genome of Hylurgini was less than C, which was consistent with the results of other published Scolytinae [72].

In the 13 PCGs of seven mitochondrial genomes, TCG and TTG were also used as the start codons in addition to the standard ATN start codon. The COI gene of T. minor was taken TCG as the start codon, while the mitochondrial genomes of other bark beetles have not been reported, but the COI gene of other insects, such as Diptera, has the same occurrence [73, 74]. TTG was the start codon of the ND1 of T. yunnanensis, T. brevipilosus, H. micklitzi and T. piniperda, which also occurs on the ND1 gene of the genus Ips [72]. This study also discovered stop codons, including TAG, T residues, and TA residues, in addition to TAA. TAG was the stop codon of Cytb, ND4L, ND1 and ND3, which also occurred in the PCGs of the published species of the Scolytinae [72, 75]; ND5 of H. ligniperda was terminated by TA residue. COII, ND5, ND4 and ND1 all are terminated with a T residue. This is also consistent with the mitochondrial genome of other published bark beetles [72].

The total AT content of the 13 PCGs ranged from 71.6% to 77.9%, higher than the average AT content of the 29 published mitochondrial genome PCGs we referred to: 70.37% (S2 Table). We also compared our nucleotide composition of the codon position of the concatenated PCGs with other published related species. The results of H. micklitzi, H. ligniperda, T. minor, T. yunnanensis, and T. piniperda were consistent with the published related species such as Hylastes and Ips. The content of the third codon positions was higher than that of the first and the second codon positions (S2 Table). The AT-skew and GC-skew values of PCGs of seven mitochondrial genomes were negative, indicating that the number of base T was greater than A. The number of base C was greater than G in PCGs, which was consistent with the published results of the tribe Ipini and Hylastini [72].

RSCU is the ratio between the frequency at which a codon is observed and the expected frequency at which the codon of any particular amino acid is equally used [76]. Thus, RSCU directly exhibits a using deviation between synonymous codon and uniform. RSCU = 1 indicates that the codon is randomly used (unbiased), RSCU > 1 suggests that the codon is used more frequently (biased), and RSCU < 1 indicates that the codon is used less frequently [77]. In the seven mitochondrial genomes, the number of synonymous codons with high using frequency was 26 (T. yunnanensis and T. piniperda), 28 (H. micklitzi, T. brevipilosus and H. ligniperda), and 30 (T. minor), 32 (D. valens), indicating a preference for these codons in their respective species. This indicates that species preferentially select optimal synonymous codons, as some chosen codons are more frequently found at conserved places [78].

Only 21 tRNA genes were detected in four of the seven sequenced mitochondrial genomes, and the missing gene was tRNA^Ile. This phenomenon has also occurred in other species of Scolytinae [79]. The loss of tRNA^Ile is due to the sequencing method. The second-generation sequencing sometimes fails to detect the AT-rich area, resulting in the loss of the gene near the AT-rich area. In the insect mitochondrial genome, tRNA^SER(AGN) usually misses the DHU arm rather than the classic cloverleaf structure. This phenomenon has also been observed in the mitochondrial genomes of other species of Scolytinae, e.g., the genus of Ips [72]. According to the results, the base mismatch in the secondary structure of tRNA mainly occurred in the DHU arms, and little in the Anticodon arms. Consequently, we can infer that various regions of tRNA exhibit distinct conservative traits, with the Anticodon arm being the most conserved. In addition, most mutation sites were located on the ring, while fewer were on the arm, indicating that the stem was more conservative.

4.2 Phylogeny of Hylurgini

The phylogenetic relationships among some taxa of Scolytinae were still unclear. For example, the tribe Dryocoetini was shown to be paraphyletic, with D. villosusu being sister to the other Dryocoetes species and the tribe Xyleborini. Among Hylurgini, our results showed that all three genera exhibit good monophyly. In the genus Tomicus, T. brevipilosus, T. piniperda and T. minor clustered into a monophyletic branch, which sister to T. yunnanensis. The T. brevipilosus and T. piniperda clustered into a monophyletic branch, separated from T. minor.

Hylurgini was sister to the tribe Hylastini in our phylogenetic analysis, aligning closely with the classification based on morphological characteristics [9]. The position of Dryocoetes villosus was undecided. Jordal [80] and Pistone [81] also indicated that the genus Dryocoetes was not monophyletic by molecular phylogeny and constitutes at least two sister groups, which requires a revision of it.

The genetic distance data of 37 species of beetles calculated by Mega 11 are shown in S3 Table. T. piniperda is comparatively more distantly related to H. ligniperda in the Hylurgus genus. H. ligniperda is more closely related to T. yunnanensis, a member of the Tomicus genus. T. minor is the most distantly related to T. yunnanensis and is distantly related to three other beetle species in the same genus. The results were not consistent with the phylogenetic results. In the phylogenetic results, T. yunnanensis was the most distant from the other three species of the same genus. T. brevipilosus is closer to T. piniperda than T. yunnanensis and T.minor. D. valens is most closely related to T. piniperda in the genus Tomicus and Hylurgus, and most distantly related to H. ligniperda. Based on the analysis of the aforementioned results, it is possible to tentatively conclude that the Hylurgini beetles located in the same region are not closer to the genetic distance. Although their ecological niches are much closer, they have no obvious connection. However, since we only discussed a limited number of data of the Hylurgini, there is no evidence of other tribes, so further in-depth research is needed.

5. Conclusion

We analysed the structure and base composition, relative synonymous codon usage of protein-coding genes, secondary structure of tRNAs and synonymous substitution rate of the mitochondrial genomes of seven bark beetles. The conserved structure of the subfamily Scolytinae’s mitochondrial genome may help us elucidate the phylogenetic relationships at a relatively high taxonomic level. We constructed a phylogenetic tree based on its mitochondrial genome data. The phylogenetic analysis was conducted to understand the evolutionary relationships within the Hylurgini tribe and Scolytinae. The taxonomic position of Hylurgini is further clarified, as well as its relationship to other sister groups. The mitochondrial genome of Hylurgini will facilitate our search for more reliable regions to develop molecular markers, and not just the commonly used COI genes. The complex co-existence phenomenon of the Hylurgini is present not only in the same genus but also between different genera (native and non-native). This phenomenon complicates the identification of bark beetles further. The novel molecular markers will facilitate the challenging species identification of the Hylurgini.

Supporting information

S1 Table. The species information from GeneBank used in the article.

https://doi.org/10.1371/journal.pone.0313448.s001

(DOCX)

S2 Table. Base composition of mitochondrial genomes of 37 species.

https://doi.org/10.1371/journal.pone.0313448.s002

(XLSX)

S3 Table. Genetic distance of 37 species of beetles.

https://doi.org/10.1371/journal.pone.0313448.s003

(XLS)

S4 Table. Organization of the mitochondrial genome of Dendroctonus valens.

https://doi.org/10.1371/journal.pone.0313448.s004

(DOCX)

S5 Table. Organization of the mitochondrial genome of Hylurgus ligniperda.

https://doi.org/10.1371/journal.pone.0313448.s005

(DOCX)

S6 Table. Organization of the mitochondrial genome of Hylurgus micklitzi.

https://doi.org/10.1371/journal.pone.0313448.s006

(DOCX)

S7 Table. Organization of the mitochondrial genome of Tomicus brevipilosus.

https://doi.org/10.1371/journal.pone.0313448.s007

(DOCX)

S8 Table. Organization of the mitochondrial genome of Tomicus piniperda.

https://doi.org/10.1371/journal.pone.0313448.s008

(DOCX)

S9 Table. Organization of the mitochondrial genome of Tomicus minor.

https://doi.org/10.1371/journal.pone.0313448.s009

(DOCX)

S10 Table. Organization of the mitochondrial genome of Tomicus yunnanensis.

https://doi.org/10.1371/journal.pone.0313448.s010

(DOCX)

S11 Table. The data of dN, dS and dN/dS boxplot.

https://doi.org/10.1371/journal.pone.0313448.s011

(XLSX)

S12 Table. The data of heatmap.

https://doi.org/10.1371/journal.pone.0313448.s012

(XLSX)

S13 Table. World distribution of seven Hylurgini species.

https://doi.org/10.1371/journal.pone.0313448.s013

(DOCX)

Acknowledgments

We are grateful to the staff of the various forestry departments in Yunnan Province for their help, to our partners in the laboratory for their help with specimen collection, and to the laboratory for their support of this research.

References

1. 1. Alonso-Zarazaga MA, Lyal CHC. A catalogue of family and genus group names in Scolytinae and Platypodinae with nomenclatural remarks (Coleoptera: Curculionidae). Zootaxa. 2009;2258: 1–134.

* View Article

* Google Scholar

2. 2. McKenna DD, Sequeira AS, Marvaldi AE, Farrell BD. Temporal lags and overlap in the diversification of weevils and flowering plants. Proceedings of the National Academy of Sciences. 2009; 106: 7083–7088. pmid:19365072

* View Article

* PubMed/NCBI

* Google Scholar

3. 3. McKenna DD. Temporal lags and overlap in the diversification of weevils and flowering plants: recent advances and prospects for additional resolution. American Entomolomologist. 2011;57: 54–55.

* View Article

* Google Scholar

4. 4. Bright DE. A Catalog of Scolytidae and Platypodidae (Coleoptera), Supplement 3 (2000–2010), with notes on subfamily and tribal reclassifications. Insecta Mundi. 2014;356: 1–336.

* View Article

* Google Scholar

5. 5. Bright DE. A Catalog of Scolytidae (Coleoptera), Supplement 4 (2011–2019) with an Annotated Checklist of the World Fauna (Coleoptera: Curculionoidea: Scolytidae). Gillette Museum of Arthropod Diversity Department of Agricultural Biology Colorado State University. 2021.

6. 6. Haack RA, Rabaglia RJ. Exotic bark and ambrosia beetles in the USA: Potential and current invader. Potential Invasive Pests of Agricultural Crops. 2013; 48–74.

* View Article

* Google Scholar

7. 7. Li JS, Chang GB, Song YS, Wang YW, Chang BS. Control Project on Red Turpentine Beetle (Dendroctonus valens). Forest Pest and Disease. 2001;4: 41–44 (in Chinese).

* View Article

* Google Scholar

8. 8. Farrell BD, Sequeira AS, O’Meara BC, Normark BB, Chung JH, Jordal BH. The evolution of agriculuture in beetles (Curculionidae: Scolytinae and Platypodinae). Evolution. 2001;55: 2011–2027. pmid:11761062

* View Article

* PubMed/NCBI

* Google Scholar

9. 9. Wood SL. A reclassification of the genera of Scolytidae (Coleoptera). Great Basin Naturalist Memoirs. 1986;10: 1–126.

* View Article

* Google Scholar

10. 10. Wood SL, Bright DE. A catalog of Scolytidae and Platypodidae (Coleoptera), Part 2. Taxonomic Index (Volumes A, B). Great Basin Naturalist Memoirs. 1992;3: 1–1553.

* View Article

* Google Scholar

11. 11. Bright DE. A Taxonomic Monograph of the Bark and Ambrosia Beetles of the West Indies (Coleoptera: Curculionoidea: Scolytidae). Occasional Papers of the Florida State Collection of Arthropods. 2019;12: 1–491.

* View Article

* Google Scholar

12. 12. Bright DE, Skidmore RE. A Catalog of Scolytidae and Platypodidae (Coleoptera).: Supplement 1 (1990–1994). NRC Research Press: Ottawa, ON, Canada. 1997.

13. 13. Li L, Wang H, Chai X, Wang Y, Shu N, Yang D. Study on the Biological Characteristics of Tomicus piniperda and Its Damage. Yunnan Forestry Science and Technology. 1997;79: 1–7 (in Chinese).

* View Article

* Google Scholar

14. 14. Li L, Liu H, Chen P, Li H, Langstrom B, Lieutier F. Comparison study on Ecological Characteristics of Tomicus piniperda and T. minor. Journal of West China Forestry Science. 2006;35: 1–5 (in Chinese).

* View Article

* Google Scholar

15. 15. Chen P, Li L, Liu H. Interspecific Competition between Tomicus yunnanensis and Tomicus (Col. Scolytnae) During Shoot-feeding Period in Yunnan of China. Journal of West China Forestry Science. 2009;38: 52–58 (in Chinese).

* View Article

* Google Scholar

16. 16. Li X, Zhang Z, Cao P, Wang H, Han P. Classification of Tomicus Species. Scientia Silvae Sinicae. 2012;48: 110–116 (in Chinese).

* View Article

* Google Scholar

17. 17. Wang J. Chemical ecological relationships of three Tomicus species. Chinese Academy of Forestry. 2015 (in Chinese).

* View Article

* Google Scholar

18. 18. Pureswaran DS, Hofstetter RW, Sullivan BT. Attraction of the Southern Pine Beetle, Dendroctonus frontalis, to Pheromone Components of the Western Pine Beetle, Dendroctonus brevicomis (Coleoptera: Curculionidae: Scolytinae), in an Allopatric Zone. Environmental Entomology. 2008;37: 70–78.

* View Article

* Google Scholar

19. 19. Breece CR, Kolb TE, Dickson BG, McMillin JD, Clancy KM. Prescribed fire effects on bark beetle activity and tree mortality in southwestern ponderosa pine forests. Forest Ecology and Management. 2008;255: 119–128.

* View Article

* Google Scholar

20. 20. Mock KE, Bentz BJ, O’Neill EM, Chong JP, Orwin J, Pfrender ME. Landscape-scale genetic variation in a forest outbreak species, the mountain pine beetle (Dendroctonus ponderosae). Molecular Ecology. 2007;16: 553–568. pmid:17257113

* View Article

* PubMed/NCBI

* Google Scholar

21. 21. Miao ZW, Chou WM, Huo FY, Wang XL, Fang JX, Zhao MM. Biology of Dendroctonus valens in Shanxi Province. Shanxi Forestry Science and Technology. 2001;23: 34–37 (in Chinese).

* View Article

* Google Scholar

22. 22. Pfeffer A. Zentral- und westpaläarktische Borken- und Kernkäfer (Coleoptera: Scolytidae, Platypodidae). Entomologica Basiliensia. 1995;17: 5–310.

* View Article

* Google Scholar

23. 23. Faccoli M, Gallego D, Branco M, Brockerhoff EG, Corley J, Coyle DR, et al. A first worldwide multispecies survey of invasive Mediterranean pine bark beetles (Coleoptera: Curculionidae, Scolytinae). Biol Invasions. 2020;22: 1785–1799.

* View Article

* Google Scholar

24. 24. Ren L, Tao J, Wu H, Zong S, Wang C, Hua D, et al. The first discovery and infective characteristics of a major invasive pest Hylurgus ligniperda (Coleoptera: Scolytinae) in China. Scientia Silvae Sinicae. 2021;57: 140–150 (in Chinese).

* View Article

* Google Scholar

25. 25. Yan Z, Sun J, Don O, Zhang Z. The red turpentine beetle, Dendroctonus valens LeConte (Scolytidae): an exotic invasive pest of pine in China. Biodiversity and Conservation. 2005;14: 1735–1760.

* View Article

* Google Scholar

26. 26. Zhang S, Shi F, Xu Y, Tao J, Zong S. Characterization of the complete mitochondrial genome of Dendroctonus valens and elimination of nuclear mitochondrial. Journal of Applied Entomology. 2022;146: 801–812. https://doi.org/10.1111/jen.13020.

* View Article

* Google Scholar

27. 27. Ye H. Studies on attacks by Tomicus piniperda (Col. Scolytinae) on Yunnan pine trees (Pinus yunnanensis). Acta Entomologica Sinica. 1999;42: 394–400 (in Chinese).

* View Article

* Google Scholar

28. 28. Wang X, Chen P, Wang Y, Yuan R, Feng D, Li L, et al. Population Structure and Succession Law of Tomicus Species in Yunnan. Forest Research. 2018;31: 164–172 (in Chinese).

* View Article

* Google Scholar

29. 29. Johnson AJ. Phylogenomics clarifies repeated evolutionary origins of inbreeding and fungus farming in bark beetles (Curculionidae, Scolytinae). Mol. Phylogenet. Evol 2018. pmid:29860101

* View Article

* PubMed/NCBI

* Google Scholar

30. 30. Wood SL. Bark and ambrosia beetles of South America (Coleoptera: Scolytidae). Monte L. Bean Science Museum. 2007.

* View Article

* Google Scholar

31. 31. Hulcr J, Atkinson TH, Cognato AI, Jordal BH, McKenna DD. Morphology, Taxonomy, and Phylogenetics of Bark Beetles. Bark Beetles. 2015;41–84.

* View Article

* Google Scholar

32. 32. Kuschel GA. phylogenetic classification of Curculionoidea to families and subfamilies. Memoirs of the Entomological Society of Washington. 1995;14: 5–33.

* View Article

* Google Scholar

33. 33. Cameron SL. Insect Mitochondrial Genomics: Implications for Evolution and Phylogeny. Annual Review of Entomology. 2014;59: 95–117. pmid:24160435

* View Article

* PubMed/NCBI

* Google Scholar

34. 34. Li R, Zhang W, Ma Z, Zhou C. Novel gene rearrangement pattern in the mitochondrial genomes of Torleya mikhaili and Cincticostella fusca (Ephemeroptera: Ephemerellidae). International Journal of Biological Macromolecules. 2020;165: 3106–3114. pmid:33098898

* View Article

* PubMed/NCBI

* Google Scholar

35. 35. Marcela A, Ananda KPD, Graciane R, Clara AA, Frederico H, Ana TR, et al. Mitochondrial genome structure and composition in 70 fishes: a key resource for fisheries management in the South Atlantic. BMC Genomics. 2024; 215: 25. https://doi.org/10.1186/s12864-024-10035-5

* View Article

* Google Scholar

36. 36. Melo-Ximenes AA, Corvalán LCJ, Carvalho LR, Mangini TA, Sobreiro MB, Vieira LD, et al. Mitochondrion genomes of seven species of the endangered genus Sporophila (Passeriformes: Thraupidae). Genetics and Molecular Biology. 2024;47(1): e20230172. pmid:38578013

* View Article

* PubMed/NCBI

* Google Scholar

37. 37. Bittencourt-Silva GB, Kamouyiaros M, Hartigan A, Okamura B. Mitochondrial genomes for the Afrobatrachian Hyperolius substriatus (Anura: Hyperoliidae) obtained from museum specimens. Journal of Vertebrate Biology. 2024;73(24009): 24009.1–7. https://doi.org/10.25225/jvb.24009

* View Article

* Google Scholar

38. 38. Espregueira TG, Rey-Iglesia A, Campos PF. The complete mitochondrial genome of the extinct Caribbean monk seal (Neomonachus tropicalis) confirms its taxonomic position and the monophyly of the genus Neomonachus. Marine Biology. 2024;171(10): 195.

* View Article

* Google Scholar

39. 39. Feng G, Jiao Y, Ma H, Bian H, Nie G, Huang L, et al. The first two whole mitochondrial genomes for the genus Dactylis species: assembly and comparative genomics analysis. BMC genomics. 2024;25(1): 235. pmid:38438835

* View Article

* PubMed/NCBI

* Google Scholar

40. 40. Boore JL. Animal mitochondrial genomes. Nucleic Acids Research. 1999;27: 1767–1780. pmid:10101183

* View Article

* PubMed/NCBI

* Google Scholar

41. 41. Wang Y, Cao J-J, Li N, Ma G-Y, Li W-H. The first mitochondrial genome from Scopuridae (Insecta: Plecoptera) reveals structural features and phylogenetic implications. International Journal of Biological Macromolecules. 2019;122: 893–902. pmid:30412754

* View Article

* PubMed/NCBI

* Google Scholar

42. 42. Lin C-P, Danforth BN. How do insect nuclear and mitochondrial gene substitution patterns differ? Insights from Bayesian analyses of combined datasets. Molecular Phylogenetics and Evolution. 2004;30: 686–702. pmid:15012948

* View Article

* PubMed/NCBI

* Google Scholar

43. 43. Yu G, Lai S, Liao S, Cao Y, Li W, Long C, et al. Complete Mitochondrial Genome of Scolytoplatypodini Species (Coleoptera: Curculionidae: Scolytinae) and Phylogenetic Implications. Genes. 2023;14(1):162. pmid:36672903

* View Article

* PubMed/NCBI

* Google Scholar

44. 44. Guo Q, Huang W, Sang W, Chen X, Wang X. Characterization, comparative analyses, and phylogenetic implications of mitochondrial genomes among bark and ambrosia beetles (Coleoptera: Curculionidae, Scolytinae). Frontiers in Ecology and Evolution. 2023;11: 1191446.

* View Article

* Google Scholar

45. 45. Li C, Wang B, Ji Y, Huang L, Wang X, Zhao W, et al. Mitochondrial genome provides species-specific targets for the rapid detection of early invasive populations of Hylurgus ligniperda in China. BMC genomics. 2024;25(1): 90. pmid:38254044

* View Article

* PubMed/NCBI

* Google Scholar

46. 46. Normar BB, Jordal BH, Farrell BD. Origin of a haplodiploid beetle lineage. Proceedings of the Royal Society B: Biological Sciences. 1999;266: 2253–2259.

* View Article

* Google Scholar

47. 47. Kohlmayr B, Riegler M, Wegensteiner R, Stauffer C. Morphological and genetic identification of the three pine pests of the genus Tomicus (Coleoptera, Scolytidae) in Europe. Agricultural and Forest Entomology. 2002;4: 151–157.

* View Article

* Google Scholar

48. 48. Faccoli M, Piscedda A, Salvato P, Simonato M, Masutti L, Battisti A. Genetic structure and phylogeography of pine shoot beetle populations (Tomicus destruens and T. piniperda, Coleoptera Scolytidae) in Italy. Annals of Forest Science. 2005;62: 361–368.

* View Article

* Google Scholar

49. 49. Kirkendall LR, Faccoli M, Ye H. Description of the Yunnan shoot borer, Tomicus yunnanensis Kirkendall & Faccoli sp. n. (Curculionidae, Scolytinae), an unusually aggressive pine shoot beetle from southern China, with a key to the species of Tomicus. Zootaxa. 2008;1819: 25–39.

* View Article

* Google Scholar

50. 50. Ma X, Lv J, Ye H. On the population phylogeny of T. yunnanensis based on mitochondrial COI gene. Journal of Yunnan Nationalities University: Natural Sciences Edition. 2016;25: 398–405 (in Chinese).

* View Article

* Google Scholar

51. 51. Yuan K. Identification map of imported wood bark beetles. Shanghai Scientific & Technical Publishers. 2007 (in Chinese).

52. 52. Jin J-J, Yu W-B, Yang J-B, Song Y, dePamphilis CW, Yi T-S, et al. GetOrganelle: a fast and versatile toolkit for accurate de novo assembly of organelle genomes. Genome Biology. 2020;21: 2–31. pmid:32912315

* View Article

* PubMed/NCBI

* Google Scholar

53. 53. Dierckxsens N, Mardulyn P, Smits G. NOVOPlasty:de novoassembly of organelle genomes from whole genome data. Nucleic Acids Research. 2016;45: 2–9. pmid:28204566

* View Article

* PubMed/NCBI

* Google Scholar

54. 54. Bernt M, Donath A, Jühling F, Externbrink F, Florentz C, Fritzsch G, et al. MITOS: Improved de novo metazoan mitochondrial genome annotation. Molecular Phylogenetics and Evolution. 2013;69: 313–319. pmid:22982435

* View Article

* PubMed/NCBI

* Google Scholar

55. 55. Laslett D, Canback B. ARWEN: a program to detect tRNA genes in metazoan mitochondrial nucleotide sequences. Bioinformatics. 2007;24: 172–175. pmid:18033792

* View Article

* PubMed/NCBI

* Google Scholar

56. 56. Lowe TM, Chan PP. tRNAscan-SE On-line: integrating search and context for analysis of transfer RNA genes. Nucleic Acids Research. 2016;44: 54–57. pmid:27174935

* View Article

* PubMed/NCBI

* Google Scholar

57. 57. Benson G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Research. 1999;27: 573–580. pmid:9862982

* View Article

* PubMed/NCBI

* Google Scholar

58. 58. Tamura K, Stecher G, Kumar S. MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Molecular Biology and Evolution. 2021;38: 3022–3027. pmid:33892491

* View Article

* PubMed/NCBI

* Google Scholar

59. 59. Yang Z. PAML 4: Phylogenetic Analysis by Maximum Likelihood. Molecular Biology and Evolution. 2007;24: 1586–1591. pmid:17483113

* View Article

* PubMed/NCBI

* Google Scholar

60. 60. Chen C, Chen H, Zhang Y, Thomas HR, Frank MH, He Y, et al. TBtools: An Integrative Toolkit Developed for Interactive Analyses of Big Biological Data. Mol. Plant. 2020;13: 1194–1202. pmid:32585190

* View Article

* PubMed/NCBI

* Google Scholar

61. 61. Grant JR, Stothard P. The CGView Server: a comparative genomics tool for circular genomes. Nucleic Acids Research. 2008;36: 181–184. pmid:18411202

* View Article

* PubMed/NCBI

* Google Scholar

62. 62. Zhang D, Gao F, Jakovlic I, Zou H, Zhang J, Li W-X, et al. PhyloSuite: an integrated and scalable desktop platform for streamlined molecular sequence data management and evolutionary phylogenetics studies. Mol Ecol Resour. 2020;20: 348–355. pmid:31599058

* View Article

* PubMed/NCBI

* Google Scholar

63. 63. Katoh K, Standley DM. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. Molecular Biology and Evolution. 2013;30: 772–780. pmid:23329690

* View Article

* PubMed/NCBI

* Google Scholar

64. 64. Nguyen L-T, Schmidt HA, von Haeseler A, inh BQ. IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies. Molecular Biology and Evolution. 2014;32: 268–274. pmid:25371430

* View Article

* PubMed/NCBI

* Google Scholar

65. 65. 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. Systematic Biology. 2012;61: 539–542. pmid:22357727

* View Article

* PubMed/NCBI

* Google Scholar

66. 66. Kalyaanamoorthy S, Minh BQ, Wong TKF, Von Haeseler A, Jermiin LS. ModelFinder: fast model selection for accurate phylogenetic estimates. Nature Methods. 2017;14: 587–589. pmid:28481363

* View Article

* PubMed/NCBI

* Google Scholar

67. 67. Huelsenbeck JP, Ronquist F, Nielsen R, Bollback JP. Bayesian Inference of Phylogeny and Its Impact on Evolutionary Biology. Science. 2001;294: 2310–2314. pmid:11743192

* View Article

* PubMed/NCBI

* Google Scholar

68. 68. Letunic I, Bork P. Interactive Tree Of Life (iTOL): an online tool for phylogenetic tree display and annotation. Bioinformatics. 2006;23: 127–128. pmid:17050570

* View Article

* PubMed/NCBI

* Google Scholar

69. 69. Wei S-J, Shi M, Chen X-X, Sharkey MJ, van Achterberg C, Ye G-Y, et al. New Views on Strand Asymmetry in Insect Mitochondrial Genomes. PLoS One. 2010;5: 1–10. pmid:20856815

* View Article

* PubMed/NCBI

* Google Scholar

70. 70. Simon C, Frati F, Beckenbach A, Crespi B, Liu H, Flook P. Evolution, Weighting, and Phylogenetic Utility of Mitochondrial Gene Sequences and a Compilation of Conserved Polymerase Chain Reaction Primers. Annals of the Entomological Society of America. 1994;87: 651–701.

* View Article

* Google Scholar

71. 71. Yang Z, Nielsen R, Goldman N, Pedersen A-MK. Codon-Substitution Models for Heterogeneous Selection Pressure at Amino Acid Sites. Genetics. 2000;155: 431–449. pmid:10790415

* View Article

* PubMed/NCBI

* Google Scholar

72. 72. Du H-C, Fang J-X, Shi X, Zhang S-F, Liu F, Yu C-M, et al. Comparative Analysis of Eight Mitogenomes of Bark Beetles and Their Phylogenetic Implications. Insects. 2021;12: 1–12. pmid:34680718

* View Article

* PubMed/NCBI

* Google Scholar

73. 73. Krzywinski J, Grushko OG, Besansky NJ. Analysis of the complete mitochondrial DNA from Anopheles funestus: An improved dipteran mitochondrial genome annotation and a temporal dimension of mosquito evolution. Molecular Phylogenetics and Evolution. 2006;39: 417–423. pmid:16473530

* View Article

* PubMed/NCBI

* Google Scholar

74. 74. Lessinger AC, Martins Junqueira AC, Lemos TA, Kemper EL, da Silva FR, Vettore AL, et al. The mitochondrial genome of the primary screwworm fly Cochliomyia hominivorax (Diptera: Calliphoridae). Insect Molecular Biology. 2000;9: 521–529. pmid:11029671

* View Article

* PubMed/NCBI

* Google Scholar

75. 75. Xu M-F, Meng R, Shui K-J, Cai B, Lin W. The complete mitochondrial genome of Ips calligraphus (Germar 1824) (Coleoptera: Curculionidae: Scolytinae). Mitochondrial DNA Part B. 2021;6: 2494–2495. pmid:34377803

* View Article

* PubMed/NCBI

* Google Scholar

76. 76. Sharp PM, Li W-H. Codon usage in regulatory genes in Escherichia coli does not reflect selection for “rare” codons. Nucleic Acids Research. 1986;14: 7737–7749. pmid:3534792

* View Article

* PubMed/NCBI

* Google Scholar

77. 77. Shang MZ, Liu F, Hua JP, Wang KB. Analysis on codon usage of chloroplast genome of Gossypium hirsufum. Scientia Agricultura Sinica. 2011;44: 245–253.

* View Article

* Google Scholar

78. 78. Jia W, Higgs PG. Codon Usage in Mitochondrial Genomes: Distinguishing Context-Dependent Mutation from Translational Selection. Molecular Biology and Evolution. 2008;25: 339–351. pmid:18048402

* View Article

* PubMed/NCBI

* Google Scholar

79. 79. Song XM, Zhao YC, Zhao P, Ma YX, Bai M, Wang XP. The First Conserved Mitochondrial Genome of Polygraphus Poligraphus (Coleoptera: Curculionidae) and Its Phylogenetic Implications. Research Square. 2021. (accessed on 23 September, 2021).

* View Article

* Google Scholar

80. 80. Jordal BH, Kambestad M. DNA barcoding of bark and ambrosia beetles reveals excessive NUMTs and consistent east-west divergence across Palearctic forests. Molecular Ecologt Resources. 2014;14: 7–17. pmid:23919425

* View Article

* PubMed/NCBI

* Google Scholar

81. 81. Pistone D, Gohli J, Jordal BH. Molecular phylogeny of bark and ambrosia beetles (Curculionidae: Scolytinae) based on 18 molecular markers. Systematic Entomology. 2017;43: 387–406.

* View Article

* Google Scholar

Citation: An N, Yuan Y, Ge S, Zhang X, Ren L, Roques A, et al. (2024) Seven mitochondrial genomes of tribe Hylurgini (Coleoptera: Curculionidae: Scolytinae) in Eurasia and their phylogenetic analysis. PLoS ONE 19(11): e0313448. https://doi.org/10.1371/journal.pone.0313448

About the Authors:

Na An

Roles: Data curation, Formal analysis, Writing – original draft

Affiliations: Beijing Key Laboratory for Forest Pest Control, College of Forestry, Beijing Forestry University, Beijing, China, IFOPE, Sino-French Joint Laboratory for Invasive Forest Pests in Eurasia, INRAE URZF and Beijing Forestry University, Beijing, China

ORICD: https://orcid.org/0009-0007-6384-8745

Yuan Yuan