Many species from the family of Lucanidae (stag beetles) are facing conservation concerns in many regions of the world. Some stag beetles are used as flagship species to raise public awareness of their protection (New, 2018). Understanding the phylogenetic relationships among species of Lucanidae will be helpful to reveal the evolutionary history of this special group and conduct conservation in practice. Previous studies have tried to construct the phylogenetic relationships among Lucanidae using partial mitochondrial and nuclear genes (Hosoya & Araya, 2005; Kim & Farrell, 2015). With the development of next-generation sequencing, it is possible to get more molecular markers for phylogenetic analysis to get more robust relationships (Fagua et al., 2018; Li et al., 2015).
The mitochondrial genome is a double-stranded circular molecule. Due to its features of material inheritance, stability of gene content and easy sequencing, it has been widely used in phylogenetic inference in many groups of animal from higher levels to lower levels (Li et al., 2016; Zheng et al., 2018). Currently, 20 mitochondrial genomes were used from the family of Lucanidae, representing four tribes, 14 genera (Table 1). Compared to the number of known species in Lucanidae, the sequenced mitochondrial genomes are still limited.
|Family||Species||GenBank Accession number||References|
|Lucanidae||Cyclommatus vitalisi||MF037205||Liu et al. (2017)|
|Dorcus curvidens hopei||MF612067||Chen et al. (2018)|
|Dorcus hansi||MF621709||Direct submission|
|Dorcus parallelipipedus||KT876887||Linard et al. (2016)|
|Lucanus cervus||MN580549||This study|
|Lucanus fortunei||MF614013||Direct submission|
|Lucanus mazama||FJ613419||Sheffield et al. (2009)|
|Macrodorcas seguyi||MF612068||Chen et al. (2018)|
|Neolucanus maximus||MF401425||Direct submission|
|Nigidionus parryi||KP987576||Direct submission|
|Nigidius sp||JX412771||Direct submission|
|Odontolabis cuvera fallaciosa||MF908524||Wang et al. (2018)|
|Prosopocoilus blanchardi||KF364622||Kim et al. (2015)|
|Prosopocoilus confucius||KU552119||Lin et al. (2017)|
|Prosopocoilus gracilis||KP735805||Wu et al. (2015)|
|Pseuderhaetus sinicus||KP987575||Direct submission|
|Prismognathus prossi||MF614014||Jing et al. (2018)|
|Rhaetus westwoodi||MG159815||Jing et al. (2018)|
|Serrognathus platymelus||MF612070||Direct submission|
|Sinodendron yunnanense||KP735804||Lin et al. (2017)|
|Scarabaeidae||Cheirotonus jansoni||NC023246||Shao et al. (2014)|
|Protaetia brevitarsis||NC023453||Kim et al. (2014)|
|Rhopaea magnicornis||NC013252||Cameron et al. (2009)|
The stag beetle L. cervus is one of the species that is in a protected status in many European countries. This species has been included in Annex II of the EU Habitats Directive since 1992 (Council Directive 92/43/EEC of 21 May 1992 on the Conservation of Natural Habitats and of Wild Fauna and Flora) (Bardiani et al., 2017), and the European Union finances “Life” Projects to protect the species every year. Nevertheless, populations of this stag beetle have dramatically declined in recent years in several European countries, mainly due to fragmentation and loss of suitable habitats (Campanaro et al., 2016). L. cervus is the largest European beetle and is widely distributed in Europe (Harvey et al., 2011). It is noteworthy that L. cervus spends most of its life in larval and pupal stage; its saproxylic larva feeds in rotten wood or roots in deciduous broad-leaved forests, in lowland and medium-altitude areas (Tini et al., 2017). Previous works revealed that the species shows a similar life history across its range, but the habitat conditions in different European countries (such as climate, temperature, humidity, and food availability) significantly affects the larval life duration and also the adult body size (Harvey et al., 2011). The larvae show a marked increase in size in favorable conditions; the adult, especially in male specimens, can show strong morphological variability in size and shape (Romiti et al., 2017).
In certain areas of the S. Mediterranean region (e.g., Latium in Italy), L. cervus can be morphologically confused and can even have hybrids with the congeneric L. tetraodon (a species not included in protection lists). In some areas of Central Italy, L. cervus has a sympatric occurrence with the closely related species L. tetraodon, and individuals with a mosaic of morphological traits can be found, making the species assignment on a simple morphological basis nearly impossible. More or less similar problems can raise at the south-eastern borders of the Palearctic distribution of L. cervus (e.g., in Turkey or Near East) where populations of other closely related species of Lucanus converge (Cox et al., 2013).
In this study, we sequenced the complete mitochondrial genome of L. cervus using next-generation sequencing; we inferred phylogenetic relationships among 20 stag beetle species. The aim of this study is to contribute to research on phylogeny of the family Lucanidae and to provide genomic information that could be useful for better management and conservation strategies that impact on this species.
Materials and Methods
Sample collection and DNA extraction
The voucher specimen of L. cervus was collected in Ukraine in July 2017 and deposited in the Museum of Anhui University with the accession number Lu166. Total genomic DNA was extracted from the muscle of L. cervus using the Qiagen DNAeasy Kit. The sequence was submitted to GenBank and assigned Accession Number MN580549 and converts into graphical maps utilized Organellar Genome DRAW in the GenBank format (Greiner, Lehwark & Bock, 2019).
Polymerase chain reaction amplification, and sequencing
Polymerase chain reaction (PCR) amplification reactions for cox1, cytb, and rrnl were carried out in 25 μL volumes containing 2 μL template DNA, 12.5 μL 2 × EasyTaq SuperMix (+dye), 1 μM of each primer (forward and reverse), and 8.5 μL sterile double-distilled water. Three fragments were amplified using common primers for L. cervus (Table 2). The PCR amplifications were performed under the conditions as previously described in Lin et al. (2017). Sanger sequencing was used to obtain the fragments of cox1, cytb and rrnl. A library was prepared using Truseq nano DNA kit (Illumina) with an insert size of 450 bp, and sequenced on the Illumina HiSeq 2,000 platformat Berry Genomics, Beijing, China. Raw reads were trimmed using Trimmomatic, with matched to the adaptor sequence >15 bp, poly-Ns (>15 bp Ns) or >75 bp bases with quality score ≤3 (Bolger, Lohse & Usadel, 2014) and we obtained 98,22,905 clean 250 bp paired-end reads with the Q30 = 93.25.
|Gene||Primer name||Sequence (5′–3′)||Reference|
|cox1||COI–F1||CAACATTTATTTTGATTTTTTGG||Simon et al. (1994)|
|COI–R1||TCCAATGCACTAATCTGCCATATTA||Simon et al. (1994)|
|cytb||Cytb–F2||GAGGAGCAACTGTAATTACTAA||Balke, Ribera & Vogler (2004)|
|Cytb–R2||AAAAGAAARTATCATTCAGGTTGAAT||Balke, Ribera & Vogler (2004)|
|rrnl||16S–F1||CCGGTTTGAACTCAGATCATG||Hosoya, Honda & Araya (2001)|
|16S–R1||TAATTTATTGTACCTTGTGTATCAG||Hosoya, Honda & Araya (2001)|
Genome assembly, annotation and analysis
High-quality reads were de novo assembled using IDBA-UD (Peng et al., 2012) with the parameters: minimum k value 80, similarity threshold 98%, and maximum k value 240. The cox1 (555 bp), cytb (404 bp) and rrnl (865 bp) fragments of L. cervus were used to identify mitochondrial assemblies using BLAST searches with ≥98% similarity (Altschul et al., 1990). To verify the accuracy of the assembly, clean reads were mapped onto the obtained fragments using “Map to reference” option of Geneious Prime 2019.1.1 (https://www.geneious.com) with maximum mismatches per read 2%; maximum ambiguity two; minimum overlap identity 97%; minimum overlap 100 bp; and no gaps. When genome was assembled in full length, the two ends of the contig overlapped, indicating circular organization of the mitochondrial genome. Finally, we obtained the mitochondrial genome of L. cervus with the mean coverage of 252.
The mitochondrial genome sequence was annotated using the MITOS web server (Bernt et al., 2013). tRNA genes and their secondary structures were inferred using tRNAscan-SE v2.0 (Lowe & Chan, 2016). In addition to 16S ribosomal RNA (rrnl, lrRNA), and 12S ribosomal RNA (rrns, srRNA), trnS1 (TCT) also determined according to sequence similarity with related species because of can’t identified by tRNAscan-SE. The codon usage, nucleotide compositions of PCGs were calculated with MEGA 7 (Kumar, Stecher & Tamura, 2016). Composition skew analysis was conducted according to formulas AT skew = (A − T)/(A + T) and GC skew = (G − C)/(G + C) (Perna & Kocher, 1995).
We retrieved 19 complete or near complete mitogenomic sequences from GenBank (Table 1) and added a newly sequenced L. cervus generating a dataset of 20 species. Three mitochondrial genomes from the family Scarabaeidae were used as outgroups. Twenty species represent 14 genera of Lucanidae. The lacked genes were treated as missing data in mitochondrial genomes of Dorcus parallelipipedus (lack of rrnl), Nigidius sp. (lack of rrns), and Nigidionus parryi (lack of nad2, cox1, rrns, rrnl). The dataset containing nucleotide sequences of 13 PCGs-condon12 with the third position removed and two rRNA genes (rrns and rrnl) of 22 species. Each PCG was aligned individually based on codon-based multiple alignments using MEGA 7 (Kumar, Stecher & Tamura, 2016). PCG12 was produced by removing the third codon with MEGA 7 (Kumar, Stecher & Tamura, 2016). Two rRNA genes (rrnl and rrns) was aligned individually using MAFFT 7 server with the G-INS-i strategy (Katoh, Rozewicki & Yamada, 2017; Kuraku et al., 2013), and we used Gblocks v0.91b Server (Castresana, 2000; Talavera & Castresana, 2007) to select conserved blocks from multiple alignments. Final, we concatenated alignments using Geneious Prime 2019.1.1 (https://www.geneious.com). The PCG12RNA dataset was partitioned using PartitionFinder 2 (Lanfear et al., 2017) for maximum likelihood (ML) analyses.
Bayesian inference (BI) and ML analyses were conducted using PhyloBayes MPI 1.5a (Lartillot, Lepage & Blanquart, 2009) and IQ-TREE web server, respectively. The BI analysis was carried out on the CIPRES Science Gateway (Miller, Pfeiffer & Schwartz, 2011). We chose the site-heterogeneous mixture model (CAT + GTR) (Song et al., 2016). Two independent chains starting from a random tree were run for 20,000 cycles, with trees being sampled every 10 cycles. The initial 25% trees of each MCMC run were discarded as burn-in. A consensus tree was computed from the remaining 1,500 trees combined from two runs, and the two runs converged at a maxdiff of less than 0.1. The best scheme for ML analyses see Table S1. For ML analyses, the “Auto” option was set under optimal evolutionary models, and the phylogenetic trees were constructed using an ultrafast bootstrap approximation approach with 10,000 replicates. Phylogenetic trees were viewed and edited in Figtree v1.4.3.
Genome organization and base composition
The complete mitochondrial genome of L. cervus is 20,109 bp in length. It is a closed circular molecule (Fig. 1), consisting of 22 tRNAs, two ribosomal RNA genes (rrnl and rrns), 13 PCGs and one control region as other typical stag beetles (Lin et al., 2017; Liu et al., 2019; Wu et al., 2015). Overall the mitogenome consisted of 37.48% A, 32.45% T, 19.05% C and 11.02% G with a highly biased A + T content of 69.93% (Table 3). Compared with L. mazama and L. foutunei, L. cervus has higher A + T content, especially in the control region. But the A + T content of L. cervus is at a medium level within the Lucanidae which has the variable base composition (Chen et al., 2018). Additionally, there is a negative GC skew, and a positive AT skew of L. cervus as other stag beetles (Chen et al., 2018; Lin et al., 2017; Liu et al., 2019, 2017; Jing et al., 2018; Wu et al., 2015). The bias of base composition has important reference value for studying the mechanism of mitochondrial genome replication and transcription (Wei et al., 2010).
|Region||Length (bp)||T (%)||C (%)||A (%)||G (%)||A + T (%)||AT skew||GC skew|
PCGs and codon usage
In PCGs, four (nad4, nad4l, nad5, nad1) of the 13 PCGs were coded on the N-strand, with the other nine genes (cox1, cox2, cox3, atp8, atp6, nad2, nad3, nad6, and cytb) were coded on the J-strand. Among the 13 PCGs, the longest was the nad5 gene and the shortest was the atp8 gene. The start codons of cox1 are AAT whereas other 12 PCGs are ATN codons (Table 4). Seven of the 13 PCGs shared the typical termination codons TAA and TAG, while others use TA residue or a single T as the terminator codons (Table 4). It is generally accepted that incomplete codon structures signal a halt of protein translation in insects and other invertebrates (Cheng et al., 2016).
|Gene||Strand||Region||Length (bp)||Start codon||Stop codon||Anticodon||Intergenic nucleotides (bp)|
tRNA and rRNA genes
All of the 22 tRNAs had a total length of 1,426 bp and range from 61 to 71 bp (Table 4), eight of the 22 tRNA-coding genes were located on the N-strand and others were located on the J-strand. Secondary structures predicted by the tRNA scan-SE suggested that all the tRNA genes in L. cervus adopted a typical clover-leaf structure, expect for trnS1 (TCT) is absent due to the deficiency of the dihydrouridine arm, which is a typical feature of metazoan mitochondrial genomes (Cameron, 2014). The length of rrnl and rrns were 1,252 bp and 806 bp, respectively (Table 4).
The control region of L. cervus was located between trnI and rrns genes as normally with the length of 5516 bp; The A + T contents, AT-skew and GC-skew is 70.59%, 0.14 and −0.23, respectively. There were seven poly-T (≥7) stretch, 24 poly-A (≥7) stretch, and one poly-TA (≥7) sequence in the long control region. Furthermore, two tandem repeats were found by online Tandem repeats finder (Benson, 1999), both of which were repeated three times; the length of the consensus sequence was 272 bp, 278 bp, respectively.
Including the newly sequenced mitochondrial genome of L. cervus, a total of twenty mitochondrial genomes from Lucanidae were used for phylogenetic analysis to analyze their phylogenetic relationships. Both BI and ML analyses consistently showed phylogenetic relationships among Lucanidae (Fig. 2). Sinodendron yunnanense is an early branch in Lucanidae (BPP = 1, MLB = 100). Lucanini was not monophyletically supported, and the earliest branch lineage was comprised of genera Neolucanus and Odontolabis. Prismognathus and Cyclommatus were closely related to Lucanus, they clustered into a lineage and sister to Dorcini. Additionally, L. cervus and L. fortunei clustered into a lineage (BPP = 0.7, MLB = 73) and sister to L. mazama (BPP = 1, MLB = 100).
The control region is the most important non-coding region in the mitochondrial genome with extremely abundant A + T content, and the length variation is very large (Zhang & Hewitt, 1997; Zhang, Szymura & Hewitt, 1995), even among species having a close genetic relationship. L. cervus has a control region with the length of 5,516 bp, obviously longer than other Lucanini species reported in our previous work (Chen et al., 2018; Lin et al., 2017; Liu et al., 2019, 2017; Jing et al., 2018; Wu et al., 2015), causing its total mitochondrial genome to be significantly longer than others.
This study presents consistent phylogenetic relationships basing BI and ML methods. Overall, there was no apparent effect of long-branch attraction within the ingroup. Most of our findings based on BI and ML were congruent with the phylogenetic analyses based on a combination of several mitochondrial genes and nuclear ribosomal genes (Kim et al., 2015). However, there were controversial relationships, especially in the lower taxonomic levels. For example, the phylogenetic status of genera Neolucanus and Odontolabis in our results were different from previous results generated from multiple fragments (Kim et al., 2015). Prosopocoilus gracilis has been classified into Dorcus (s.l.) rather than Prosopocoilus (Lin et al., 2017). Our results showed that mitochondrial genomes sequences are powerful in relationships inference within Lucanidae. The sequencing and assembly of the mitochondrial genome will facilitate future works of mitochondrial genome sequencing (Bourguignon et al., 2017; Crampton-Platt et al., 2015). Increased taxa sampling and genome sequencing will help to resolve the classification problems within Lucanidae.
In our study, the phylogenomic analysis supports the morphological conclusion on relationships of Lucanidae. Although our data could not solve all the phylogenetic relationships within Lucanidae, this study can be helpful for future research on the Lucanidae phylogeny.