Next Article in Journal
Association Between Single-Nucleotide Polymorphism rs2287886 of CD209 Gene and Clinical Severity of COVID-19 in Unvaccinated Brazilian Patients
Previous Article in Journal
Comparative Chloroplast Genomics of Ten Collabieae Species Including Three Novel Genomes
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Genes
Volume 16
Issue 9
10.3390/genes16091030
genes-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Assembly of Mitochondrial Genome of Oriental Plover (Anarhynchus veredus) and Phylogenetic Relationships Within the Charadriidae

by
Baodong Yuan
1,
Xuan Shao
2,
Lingyi Wang
2,
Jie Yang
2,
Xiaolin Song
2 and
Huaming Zhong
2,*
1
College of Agriculture and Biology, Liaocheng University, Liaocheng 252000, China
2
College of Biology and Food, Shangqiu Normal University, Shangqiu 476000, China
*
Author to whom correspondence should be addressed.
Genes 2025, 16(9), 1030; https://doi.org/10.3390/genes16091030
Submission received: 17 July 2025 / Revised: 12 August 2025 / Accepted: 28 August 2025 / Published: 29 August 2025
(This article belongs to the Section Animal Genetics and Genomics)
Browse Figures
Versions Notes

Abstract

Background: Traditional morphology-based classification of the Oriental Plover (Anarhynchus veredus) is inconsistent with molecular evidence, underscoring the necessity of incorporating molecular data to elucidate its evolutionary relationships within Charadriidae. Methods: Here, we present the first complete mitochondrial genome of A. veredus by Illumina NovaSeq Sequencing and explore its evolutionary implications within Charadriidae. Results: The mitogenome spans 16,886 bp and exhibits conserved structural features typical of Charadriidae, including gene order, overlapping coding regions, and intergenic spacers. Nucleotide composition analysis revealed a GC content of 44.3%, aligning with other Charadriidae species (44.5–45.8%), and hierarchical GC distribution across rRNA, tRNA, and protein-coding genes (PCGs) reflects structural and functional optimization. Evolutionary rate heterogeneity was observed among PCGs, with ATP8 and ND6 showing accelerated substitution rates (Ka/Ks = 0.1748 and 0.1352) and COX2 under strong purifying selection (Ka/Ks = 0.0678). Notably, a conserved translational frameshift in ND3 (position 174) was identified. Phylogenetic analyses (ML/NJ) of 88 Charadriiformes species recovered robust topologies, confirming that the division of Charadriidae into four monophyletic clades (Pluvialis, Vanellus, Charadrius, and Anarhynchus) and supporting the reclassification of A. veredus under Anarhynchus. Conclusions: This study resolves the systematic position of A. veredus and highlights the interplay between conserved mitochondrial architecture and lineage-specific adaptations in shaping shorebird evolution.

1. Introduction

Shorebirds (Charadriiformes) are an ecologically diverse and globally distributed order of birds, comprising approximately 390 species, and represent one of the most ecologically and morphologically diverse avian radiations [1,2]. The family Charadriidae, comprising plovers and lapwings, represents a globally distributed group of shorebirds occupying diverse ecosystems from coastal wetlands to arid grasslands. These medium-sized waders exhibit remarkable ecological adaptability, as evidenced by their radiation across habitats spanning Arctic tundra to tropical mudflats [3]. Among them, the Oriental Plover (Anarhynchus veredus) stands out as a long-distance migrant that breeds in Mongolian grasslands and winters in northern Australia. This species demonstrates unique ecological specialization through its sexually dimorphic breeding plumage and adaptations particularly suited to sparse vegetation zones where cryptic coloration enhances predator avoidance [4]. Although currently classified as Least Concern by the IUCN, its dependence on ephemeral breeding habitats renders it vulnerable to climate-driven aridification and anthropogenic landscape modifications.
Recent molecular systematic studies have substantially revised our understanding of Charadriidae phylogeny over the past two decades, particularly regarding genus-level classifications and polyphyly resolution [5,6,7,8,9]. Dos Remedios et al. (2015) sampled two mitochondrial genes (COI and ND3) and four nuclear loci (ADH5, FIB7, MYO2, and RAG1) from 29 Charadrius species [7]. Their MCC tree divided the genus Charadrius into two major clades (Charadrius clade I and II, i.e., CRD I and CRD II), which were further categorized into six minor clades (Clades a–f) of sister species. Among these, the Oriental Plover was clustered into the CRD II-b clade. Phylogeny result from eight mitochondrial and two nuclear loci further support that the Oriental Plover belongs to CRD II [10]. Černý & Natale utilized 27 genetic loci and a matrix of 69 skeletal characters to address the relationships of most Charadriiformes species [11]. Sun et al. (2024) constructed a phylogenetic tree based on complete mitogenomes using sequences of 13 mitochondrial protein-coding genes (CDSs) from 114 available Charadriiformes mitogenomes [12]. Although both studies strongly support the recognition of three major shorebird clades and the division of Charadriidae into monophyletic genera (including Anarhynchus, Vanellus, Charadrius, and Pluvialis), the Oriental Plover was not included in either analysis.
Mitochondrial genomes offer unique advantages for resolving such taxonomic uncertainties. Their maternal inheritance circumvents complexities of biparental recombination, while differential evolutionary rates across genomic regions enable phylogenetic resolution at multiple timescales: rapidly evolving control regions elucidate recent divergences, whereas conserved protein-coding genes like COX1 retain deep phylogenetic signals [13,14]. The compact size (16–18 kb) of animal mitogenomes, combined with heterogeneous evolutionary rates among their 37 genes, provides multiple markers for robust branch support estimation [15,16]. However, the lack of a complete mitogenome for A. veredus highlights the need for these data to resolve its phylogenetic relationships within the Charadriidae.
In this study, we assembled and annotated the first complete mitochondrial genome of A. veredus using Illumina NovaSeq technology. To investigate the interspecific variation in Charadriidae, we compared mitogenomes from 13 Charadriidae mitogenomes to identify lineage-specific adaptations in base composition, codon usage, gene arrangement, and selection pressures. Furthermore, we reconstructed a mitogenome-based phylogeny to clarify the evolutionary position of A. veredus within Charadriidae.

2. Materials and Methods

2.1. Specimen Collection and DNA Extraction

One A. veredus individual was collected on 8 July 2024, in Weihai City, Shandong Province, China (37.19° N, 122.23° E). The species identification was made based on morphological characteristics, following a Field Guide to the Birds of China [17]. Leg muscle was sampled and preserved in 95% ethanol. All experimental procedures were conducted in accordance with the guidelines established by the Ethics Committee of the Animal Experiments of Shangqiu Normal University (Shangqiu City, Henan, China) and were approved under protocol number 2024016. Total genomic DNA was extracted from muscle tissue samples using the E.Z.N.A.® Tissue DNA Kit (Omega, Norcross, GA, USA), following the manufacturer’s protocol.

2.2. Library Construction and Illumina NovaSeq Sequencing

DNA integrity was verified by 1% agarose gel electrophoresis, and quantification was performed using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Sequencing libraries were prepared from 1 μg of high-quality genomic DNA using the TruSeq™ Nano DNA Sample Prep Kit (Illumina, San Diego, CA, USA). Genomic DNA was fragmented to a target size of 300–500 bp using the Covaris M220 ultrasonicator (Covaris, Shelton, CT, USA). The fragmented DNA underwent three consecutive enzymatic reactions: (1) end repair to generate blunt-ended fragments, (2) 3′ adenylation to facilitate adapter ligation, and (3) ligation of uniquely indexed Illumina adapters using the TruSeq™ Nano DNA Sample Prep Kit. The adapter-ligated DNA was amplified through 8 cycles of PCR amplification. PCR products were size-selected (300–500 bp) by electrophoresis on 2% Certified Low Range Ultra Agarose (Bio-Rad, Hercules, CA, USA) at 120 V for 40 min, followed by gel extraction using the QIAquick Gel Extraction Kit (Qiagen, Hilden, Germany). Library quantification was performed using the TBS380 PicoGreen dsDNA Assay Kit (Invitrogen, Carlsbad, CA, USA) with a Qubit 3.0 Fluorometer (Thermo Fisher Scientific, Waltham, MA, USA). Cluster generation was achieved through bridge amplification on an Illumina cBot system using the TruSeq PE Cluster Kit v3-cBot-HS (Illumina, San Diego, CA, USA). Paired-end sequencing (2 × 150 bp) was conducted on the Illumina NovaSeq 6000 platform (Illumina, San Diego, CA, USA) with the TruSeq SBS Kit v3 (300 cycles). Image analysis and base calling were performed using NovaSeq Control Software v1.7.0 (Illumina, San Diego, CA, USA).

2.3. Quality Control and Preprocessing of the Sequencing Data

Raw sequencing reads were processed through a multi-stage quality control pipeline using Trimmomatic v0.39 [18]. Adapter sequences were eliminated through automated alignment, and 5′-terminal nucleotides containing non-canonical bases (non-AGCT) were precisely excised. A sliding window algorithm (window size: 4 bp, step: 1 bp) subsequently removed terminal regions with averaged Phred scores <Q20, while reads containing >10% ambiguous nucleotides (N) underwent rigorous exclusion. Ultimately, processed reads shorter than 75 bp (<0.5× read length) were filtered through size-selection protocols.

2.4. Mitogenome Assembly and Annotation

The mitochondrial genome assembly of A. veredus was performed using GetOrganelle v1.7.5 software (https://github.com/Kinggerm/GetOrganelle, accessed on 12 September 2024) [19]. Candidate sequences were selected based on sufficient depth of coverage and longer assembly lengths, followed by alignment with the NCBI NT database to identify mitochondrial scaffolds. The selected sequences were then systematically assembled through precise overlapping regions. Subsequently, the MITOS software (http://mitos.bioinf.uni-leipzig.de/index.py, accessed on 15 September 2024) [20] was used to predict the protein-coding, tRNA, and rRNA genes of the mitochondrial genome, with the vertebrate mitochondrial code selected as the codon table. Finally, the CGView software [21] (http://stothard.afns.ualberta.ca/cgview_server/, accessed on 17 September 2024) was used to display the circular map of the genome.

2.5. Comparative Mitogenomic Analyses

The complete mitochondrial genomes of 13 Charadriidae species were selected for comparative analysis. The corresponding accession numbers are provided in Supplementary Material Table S1. The relative synonymous codon usage (RSCU) was calculated using PhyloSuite [22,23] and visualized with the ggplot2 package in R software (version 4.1.3). Nucleotide compositional biases were assessed using AT skew [(A − T)/(A + T)] and GC skew [(G − C)/(G + C)] [24]. To gain a deeper understanding of the selective pressure on protein-coding genes (PCGs), we calculated the evolutionary rates for each PCG within the Charadriidae family with PhyloSuite v1.2.3 [22,23]. Additionally, synteny analysis was conducted using Mauve software v2.4 [25], based on 13 Charadriidae mitochondrial genomes.

2.6. Phylogenetic Analyses

We first searched and retrieved available mitogenome sequences in GenBank format from the NCBI database. A total of 88 sequences from 88 Charadriiformes species, representing 44 genera across 12 families, along with the outgroup species Balearica regulorum (Gruiformes) were included in the phylogenetic analysis (Supplementary Material Table S1). PhyloSuite v1.2.3 [22,23] was used to extract the gene sequences from all 89 mitogenomes. The PCGs, 12S rRNA and 16S rRNA genes were aligned with MAFFT v7.505 [26]. For the PCGs, a codon-based alignment was performed using the ‘E-INS-i (accurate)’ strategy, while the rRNA genes were aligned under the same strategy but in normal alignment mode. Subsequently, the PCGs alignment results were refined using the codon-aware program MACSE v2.06 [27], which preserves reading frame and allows incorporation of sequencing errors or sequences with frameshifts. Finally, the aligned PCGs, 12S rRNA and 16S rRNA from the same species were concatenated together by PhyloSuite. ModelFinder v2.2.0 [28] was used to determine the best-fit partition model (Edge-unlinked) for phylogenetic analysis based on the Bayesian inference (BI) method, with the selection guided by the Bayesian Information Criterion (BIC). The model identified as the best fit for BI was GTR+F+I+G4. Bayesian inference phylogenies were inferred using MrBayes v3.2.7a [29] under a partition model (4 parallel runs, 28,000 generations), with the initial 5000 sampled data were discarded as burn-in. Additionally, neighbor-joining (NJ) phylogenetic analyses [30] were performed in MEGA X [31]. The percentage of replicate trees in which the associated taxa clustered together was determined using a bootstrap test with 10,000 replicates. Evolutionary distances were computed using the Jukes-Cantor method [32], expressed as the number of base substitutions per site. Rate variation among sites was modeled using a gamma distribution (shape parameter = 1). All ambiguous positions were removed for each sequence pair under the pairwise deletion option. The phylogenetic tree was visualized using FigTree v1.44 and further refined with Adobe Illustrator CS6 v16.0.0.

3. Results

3.1. Mitochondrial Genome Structure and Composition

We sequenced and assembled the mitogenome of A. veredus using Illumina NovaSeq technology, generating a total of 48,624,872 raw reads (Supplementary Material Table S2). The resulting sequence data were deposited in GenBank under the accession number SRR32628449. Following quality control, a total of 48,569,886 clean reads were retained, representing 7283.1 Mbp of clean data for further analysis (Supplementary Material Table S2). The A. veredus mitogenome was deposited in GenBank under accession numbers PV262314. Summary information is shown in Table 1. The A. veredus mitogenome possesses circular double-stranded DNA molecules, containing 13 PCGs, 22 tRNA genes, 2 rRNA genes. Among these, 9 genes (tRNAGLN, tRNAALA, tRNAASN, tRNACYS, tRNATYR, tRNASER, tRNAPRO, NAD6, and tRNAGLU) were located on the light strand, while the remaining 28 genes were situated on the heavy strand. The D-loop region was located between tRNAGLU and tRNAPHE (Figure 1). In addition, we identified nine overlapping coding regions and 19 intergenic spacers. The largest overlapping coding region was 10 bp, located between ATP8 and ATP6, while the largest intergenic spacer was 22 bp, positioned between tRNAPRO and ND6.
The GC nucleotide proportion in the complete mitochondrial genome of A. veredus was 44.3%, lower than the AT nucleotide proportion (Table 2). The AT skew for the complete mitochondrial genome was 0.131, while the GC skew was −0.389. In PCGs, tRNAs, rRNAs, and D-loop, the AT nucleotide proportion exceeded that of GC nucleotides. The AT skew was slightly positive, whereas the GC skew was negative (Table 2). These results indicate a higher abundance of A over T and C over G.

3.2. PCGs and Codon Usage

The initiation codon for most PCGs was ATG (N = 10), while the remaining three genes utilized alternative start codons: COX1 and ND5 used GTG, and ND3 used ATC. The termination codons were TAA (N = 7), TAG (N = 2), T-- (N = 2), and AGG (N = 2). Additionally, an extra nucleotide (C: cytosine) was present at the position 174 of the ND3 gene (Table 1). We conducted RSCU analysis to elucidate the codon usage bias of PCGs. The results revealed that Arg, Leu, Pro, Lys, and Ser were the most abundant amino acids (Figure 2). The five most prevalent codons were Arg (CGA), Leu (CUA), Pro (CCU), Lys (AAA), and Ser (UCA). The RSCU values indicated a tendency towards higher usage of A and C compared to T and G in most codons, while Gln, Cys, and Ser1 exhibited a preference for G in their codon usage.

3.3. Transfer and Ribosomal RNA Genes

The mitogenome of A. veredus contained 22 transfer RNA genes, as in most vertebrates. The total lengths of tRNAs was 1546 bp, and these tRNA genes ranged from 66–74 bp. We found that only tRNASER2(GCT) lacked the dihydrouridine (DHU) arm, and the remaining 21 tRNA genes formed a typical cloverleaf structure (Figure 3). The 12S and 16S rRNA genes on the N-strand of A. veredus mitogenome were located between tRNAPHE and tRNAVAL and tRNALEU (Table 1). Their lengths were 979 bp and 1601 bp, respectively. Both genes exhibited a negative AT skew and a positive GC skew (Table 2).

3.4. Control Region

The control region, also called the AT-rich region, is the longest non-coding region involved in mitogenomic replication and transcription. In the A. veredus mitochondrial genome, this region was located between the tRNAGLU and tRNAPHE. The length of the control region was 1321 bp, exhibiting a positive AT skew (0.051) and negative GC skew (−0.372) (Table 2).

3.5. Comparative Analysis of the Charadriidae Mitochondrial Genomes

The total length of 13 Charadriidae species mitogenomes varied from 15,723 bp (Pluvialis apricaria) to 17,074 bp (Vanellus cinereus). PCGs exhibited remarkable length conservation (11,385–11,397 bp; CV = 0.3%, Table 3). Structural RNAs exhibited moderate variation. rRNA lengths ranged from 2536 to 2583 bp (CV = 0.6%), and tRNA clusters varying between 1543 bp (A. montanus) and 1553 bp (A. leschenaultia). GC content stratification was evident across functional regions, with rRNA maintaining the highest GC levels (45.2–46.7%), followed by PCGs (44.6–46.8%) and tRNA (41.2–42.7%). Notably, species in the genus Pluvialis exhibited a higher genomic GC content (45.4–45.8%) than those in the genus Vanellus (44.6–44.9%). PCGs showed the greatest intergeneric divergence, with GC content ranging from 45.9% to 46.8% in Pluvialis and 44.8% to 45.3% in Vanellus (Table 3).
Strand asymmetry analysis revealed consistent positive AT-skew (0.131–0.153) and negative GC-skew (−0.402 to−0.374) across the entire genome (Table 3), which is in agreement with the characteristic light-strand compositional bias. Notably, rRNA genes displayed higher AT-skew (0.216–0.237) than PCGs (0.060–0.082). A notable exception was observed in Charadrius dubius and Charadrius vociferus, which exhibited positive tRNA GC-skew (0.017 and 0.005), contrasting with the consistently negative values found across other taxa. Additionally, a conserved frameshift at position 174 of the ND3 gene was observed in all 13 species.
Comparative alignment of the 13 mitochondrial genomes showed that the gene order was conserved among A. veredus and their close Charadriidae relatives (Figure 4).
To investigate the selective pressure acting up on PCGs within Charadriidae, the evolutionary rates of each PCG were calculated and compared. For all PCGs, the Ka/Ks ratios were consistently lower than 1 (Figure 5), indicating that purifying selection acted on all PCGs. ATP8 and ND6 exhibited high substitution rates (0.1748 and 0.1352, respectively), whereas COX2 showed a low evolutionary rate (0.0678).

3.6. Phylogeny Analysis

Utilizing 13 PCGs, 12S rRNA, and 16S rRNA genes, we constructed phylogenetic trees for 88 Charadriiform species using both ML and NJ methods. The resulting topologies from both methods were found to be identical, with high support bootstrap values and posterior probability (Figure 6). This consistency of trees between ML and NJ approaches suggests a robust dataset and a reliable phylogenetic structure, reinforcing the credibility of the inferred evolutionary relationships. All the Charadriiformes groups form a strictly monophyletic group and were separated from the outgroup Gruiformes, verifying the reliability of Charadriiform as an independent evolutionary branch. The results showed that the Charadriiform were divided into three suborders: Scolopaci, Lari, and Charadrii. Lari and Scolopaci form a sister group, while Charadrii constitutes a separate branch. Among Scolopaci, family Jacanidae was closely related to Rostratulidae, whereas most species were classified within Scolopacidae Family. In the suborder Lari, Family Turnicidae was the earliest-diverging lineage and is positioned on a long evolutionary branch. Meanwhile, families Glareolidae, Alcidae, Stercorariidae, and Laridae formed a distinct clade in the phylogenetic tree. The 21 species of the Charadrii suborder were classified into six families: Haematopodidae, Ibidorhynchidae, Charadriidae, Burhinidae, Pluvianellidae, and Chionididae. Within this suborder, family Burhinidae, Pluvianellidae, and Chionidae formed a well-supported clade, which was the sister group to all other members of Charadrii. Notably, the ibisbill (Ibidorhyncha struthersii) and Magellanic Plover (Pluvianellus socialis) represent the sole species within the monotypic families Ibidorhynchidae and Pluvianellidae, respectively.
The family Charadriidae comprises four main genera: Pluvialis, Vanellus, Charadrius, and Anarhynchus (Figure 6). Among these, Pluvialis represents the basal lineage, having diverged first. Following this, Vanellus diverged, while Charadrius and Anarhynchus form a sister group. Our results support the monophyly of Anarhynchus and include the following species: Oriental Plover (A. veredus), Kentish Plover (A. alexandrinus), Black-fronted Dotterel (A. atrifrons), Greater Sand Plover (A. leschenaultia), Mountain Plover (A. montanus), and Mongolian Plover (A. mongolus).

4. Discussion

In this study, we report the complete mitochondrial genome of A. veredus for the first time. The total length of the A. veredus mitogenome was 16,886 bp, which falls within the range for other Charadriidae birds (15,723–17,074 bp). The gene arrangements of the 13 Charadriidae mitogenomes were highly conserved and largely identical to those of most avian species [33,34,35]. The A. veredus mitogenome displayed a typical, highly conserved architecture characteristic of Charadriidae. Gene order, overlapping regions (e.g., the 10 bp overlap between ATP8 and ATP6), and intergenic spacers mirrored those of A. alexandrines [36] and A. atrifrons [37], suggesting minimal structural reorganization over evolutionary timescales.
Beyond structural conservation, nucleotide composition analysis revealed critical evolutionary patterns. The GC content of A. veredus mitogenome was 44.3%, aligning closely with other Charadriidae species (44.5–45.8%). These slight variations likely arose from differential mutation rates or selective constraints imposed by environmental factors, which may affect genome stability and function [38,39]. All studied Charadriidae species exhibited lower GC content than AT content, a pattern consistent with most avian mitogenomes [40,41]. The hierarchical GC distribution— characterized by high in rRNA and low in tRNA—likely reflects structural optimization. Elevated GC content in rRNA stabilizes ribosomal secondary structures through enhanced base-pairing interactions [42], while reduced GC content in tRNA may enhance D-loop flexibility during cloverleaf formation [43]. The significant GC divergence in PCGs between Pluvialis and Vanellus may reflect differential codon usage optimization, potentially associated with thermal adaptation or oxidative stress tolerance in their distinct ecological niches. The universal AT/GC skew polarity reflects conserved replication strand asymmetry [44]. However, the pronounced AT-skew in rRNA suggests transcription-driven mutational biases, as continuous transcription of rDNA could potentially increase deamination rates on the heavy strand [45]. Intergeneric comparisons indicated that Anarhynchus species exhibited higher PCGs GC-skew values (−0.399 to −0.409) than Pluvialis (−0.413 to −0.424) and Vanellus (−0.410 to −0.418), supporting their phylogenetic placement. These results underscore the balance in shorebird mitogenomic architecture between conserved functional elements and flexible non-coding regions, facilitating both metabolic stability and lineage-specific adaptations [11].
Functional constraints on mitochondrial genomes extended beyond nucleotide composition to protein-coding genes (PCGs). The PCGs of Charadriidae mitochondria exhibited high conservation, with their structure and arrangement aligning perfectly with prior studies on avian mitochondrial PCGs [33,34,35]. The conserved PCGs architecture highlights evolutionary constraints imposed by mitochondrial energy metabolism [46], while variable non-coding regions may mediate lineage-specific regulatory adaptations [13]. Among the 13 PCGs, canonical start codons (ATG) dominated (10/13), while COX1 and ND5 initiated with GTG and ND3 with ATC—a pattern consistent across all 13 Charadriidae species except for ND3 (ATT) in Killdeer (C. vociferous). These non-canonical codons may undergo post-transcriptional modification to ensure translational fidelity, a mechanism observed in avian mitochondrial systems [47]. Termination codons predominantly included TAA (7/13) and incomplete T-- (2/13), the latter resolved via mRNA polyadenylation, a ubiquitous feature of avian mitogenomes [24]. In metazoan mitochondrial genomes [48], incomplete stop codons (e.g., TA or T) are common and may be completed to TAA during mRNA maturation through post-transcriptional modification [49]. RSCU analysis revealed pronounced biases toward A/C-rich codons (e.g., Arg-CGA, Leu1-CUA), correlating with the overall A + T skew and mirroring trends in Little Ringed Plover (C. dubius) and Eurasian Oystercatcher (Haematopus ostralegus) [33]. Such codon preferences may reflect selection for translational efficiency or mutational biases during replication [50]. Evolutionary rate heterogeneity was evident: ATP8 and ND6 exhibited accelerated substitution rates (Ka/Ks = 0.1748 and 0.1352), while COX2 showed the signature of strong purifying selection (Ka/Ks = 0.0678). This result aligns with findings in Kentish Plover (A. alexandrinus), where ATP8’s functional redundancy permits higher plasticity, whereas COX2’s role in electron transport imposes strict conservation [12,36].
In addition to sequence-level conservation, we identified a notable genomic feature in A. veredus. The nad3-174 frameshift observed in A. veredus has also been found in many Archosauria-Testudines species [47,51,52,53,54]. Computational analysis of the nucleotide sequence surrounding position 174 reveals a conserved motif (TTC-CTA-GTA), matching the “slippery sequence” identified in ostrich (Struthio camelus) and turtles [54]. Specifically, the sequence forms a stem-loop structure between nucleotides 172–178 (5′-TTCCTAG-3′), facilitating ribosomal stalling and subsequent frameshifting. This mechanism skips the fourth nucleotide (position 174), merging codons 58 (TTC → Phe) and 59 (CTA → Leu) into a hybrid codon (TCT → Ser) to produce a contiguous NAD3 protein. Validated by homology-based Hidden Markov models(HMMs) [51], this finding supports the hypothesis that translational reprogramming, rather than genomic correction, is a conserved strategy in mitochondrial genome evolution.
Among the 22 tRNAs, tRNASER2(GCT) lacked the dihydrouridine hairpin structure, whereas all the remaining 21 tRNAs exhibited a canonical cloverleaf structure. The absence of a canonical cloverleaf structure in tRNASER has been observed in several animal species [36,55,56]. Several studies have shown that the absence of either the dihydrouridine arm or the thymidine–pseudouridine–cytidine (TΨC) loop in tRNASER may not impair its normal function [57,58]. These findings suggest that tRNASER2(GCT) is likely capable of performing its normal functions in A. veredus.
Our phylogenetic analyses of 88 Charadriiform species using ML and NJ methods recovered identical tree topologies, supporting the established division of Charadriiformes [11,12]. This study corroborates the division of Charadriidae into four monophyletic branches: Pluvialis, Vanellus, Charadrius, and Anarhynchus. This aligns with the Charadriidae classification framework proposed by Černý, D. and Natale, R. [11], who transferred the CRD II branch of the original Charadrius genus to the Anarhynchus genus. However, our study significantly improved branch support through a more complete mitochondrial dataset. Phylogenetic relationships among individual Charadriidae species are largely congruent with those of Sun et al. [12], though their study did not update the nomenclature for several Anarhynchus species previously categorized under Charadrius. Notably, our study supports the monophyly of Anarhynchus, which includes Oriental Plover (A. veredus), Mongolian Plover (A. mongolus), and A. leschenaultii, consistent with the classification revision of the International Ornithological Committee (IOC) based on naming priority. This study is the first to incorporate A. veredus into molecular phylogenetic analysis, unequivocally establishing its classification within Anarhynchus and supporting the IOC’s taxonomic revision. Additionally, the reclassification of the Lesser Sand Plover (C. mongolus) into two species—the Siberian Sand Plover (C. mongolus) and Tibetan Sand Plover (C. atrifrons)—is noteworthy. Finally, the basal position of Pluvialis within Charadriidae aligns with molecular systematic views that recognize Pluvialis as the independent subfamily Pluvialinae, further supporting its deep divergence (>20 Ma).

5. Conclusions

The A. veredus mitogenome exhibits conserved features relative to other Charadriidae species. Phylogenetic analyses confirm the well-established classification of Charadriiformes and support the monophyly of Anarhynchus, consistent with the IOC’s taxonomic revision. The identification of a conserved frameshift mechanism in NAD3 underscores the role of translational reprogramming in mitochondrial genome evolution. These findings clarify the systematic position of A. veredus and provide novel insights into the diversification patterns within Charadriidae.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/genes16091030/s1, Table S1: Taxonomic information and Genbank accession numbers for taxa used in the phylogenetic analysis; Table S2: Statistics of next-generation sequencing data.

Author Contributions

B.Y. wrote the main manuscript text and prepared the figures. X.S. (Xuan Shao), L.W. and J.Y. contributed to data curation, methodology, and writing—review and editing. X.S. (Xiaolin Song) contributed to data curation and methodology. H.Z. was responsible for funding acquisition, conceptualization, project administration, supervision, and writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (grant number: 32400173) and Natural Science Foundation of Shandong Province (grant number: ZR2023MC016).

Institutional Review Board Statement

All experimental procedures were conducted in accordance with the guidelines established by the Ethics Committee of the Animal Experiments of Shangqiu Normal University (Shangqiu City, Henan, China) and were approved under protocol number 2024016 on 18 June 2024.

Informed Consent Statement

Not applicable.

Data Availability Statement

The datasets generated for this study are available in the Sequence Read Archive (SRA) of the NCBI database (Accession number: SRR32628449).

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Boyd, J.H. Taxonomy in Flux: Version 3.51c. Available online: http://jboyd.net/Taxo/List9a.html (accessed on 12 July 2025).
  2. Clements, J.F.; Rasmussen, P.C.; Schulenberg, T.S.; Iliff, M.J.; Fredericks, T.A.; Gerbracht, J.A.; Lepage, D.; Spencer, A.; Billerman, S.M.; Sullivan, B.L.; et al. The eBird/Clements Checklist of Birds of the World: V2024. 2024. Available online: https://www.birds.cornell.edu/clementschecklist/download/ (accessed on 12 July 2025).
  3. Piersma, T.; De Goeij, P.; Tulp, I. An Evaluation of Intertidal Feeding Habitats from a Shorebird Perspective: Towards Relevant Comparisons between Temperate and Tropical Mudflats. Neth. J. Sea Res. 1993, 31, 503–512. [Google Scholar] [CrossRef]
  4. Murray, M.D.; Ricardo, P.L.; Pilgrim, R.L.C. Ectoparasites of Australian, New Zealand and Antarctic Birds—Raptors to Lapwings. In Handbook of Australian, New Zealand and Antarctic Birds; Marchant, S., Higgins, P.J., Eds.; Oxford University Press: Oxford, UK, 1993; pp. 959–962. ISBN 0-19-553069-1. [Google Scholar]
  5. Baker, A.J.; Pereira, S.L.; Paton, T.A. Phylogenetic Relationships and Divergence Times of Charadriiformes Genera: Multigene Evidence for the Cretaceous Origin of at Least 14 Clades of Shorebirds. Biol. Lett. 2007, 3, 205–210. [Google Scholar] [CrossRef]
  6. Colwell, M.A.; Haig, S.M. The Population Ecology and Conservation of Charadrius Plovers, 1st ed.; CRC Press: Boca Raton, FL, USA, 2019; ISBN 9781315152882. [Google Scholar]
  7. Dos Remedios, N.; Lee, P.L.M.; Burke, T.; Székely, T.; Küpper, C. North or South? Phylogenetic and Biogeographic Origins of a Globally Distributed Avian Clade. Mol. Phylogenetics Evol. 2015, 89, 151–159. [Google Scholar] [CrossRef]
  8. Livezey, B.C. Phylogenetics of Modern Shorebirds (Charadriiformes) Based on Phenotypic Evidence: Analysis and Discussion. Zool. J. Linn. Soc. 2010, 160, 567–618. [Google Scholar] [CrossRef]
  9. Qian, W.; Liu, Y.; Miao, K.; Chang, Q.; Hu, C. Taxonomic Status and Phylogenetic Relationship of the Charadriidae Family Based on Complete Mitogenomes. Curr. Genom. 2023, 24, 263–272. [Google Scholar] [CrossRef]
  10. Barth, J.M.I.; Matschiner, M.; Robertson, B.C. Phylogenetic Position and Subspecies Divergence of the Endangered New Zealand Dotterel (Charadrius obscurus). PLoS ONE 2013, 8, e78068. [Google Scholar] [CrossRef]
  11. Černý, D.; Natale, R. Comprehensive Taxon Sampling and Vetted Fossils Help Clarify the Time Tree of Shorebirds (Aves, Charadriiformes). Mol. Phylogenetics Evol. 2022, 177, 107620. [Google Scholar] [CrossRef]
  12. Sun, K.; Wang, Q.; Bian, K.; Li, F.; Tang, J.; Suo, L.; Hou, X.; Yang, C. Complete Mitochondrial Genomes of Pluvialis fulva and Charadrius dubius with Phylogenetic Analysis of Charadriiformes. Genes 2024, 15, 1642. [Google Scholar] [CrossRef]
  13. Boore, J.L. Animal Mitochondrial Genomes. Nucleic Acids Res. 1999, 27, 1767–1780. [Google Scholar] [CrossRef]
  14. Gissi, C.; Iannelli, F.; Pesole, G. Evolution of the Mitochondrial Genome of Metazoa as Exemplified by Comparison of Congeneric Species. Heredity 2008, 101, 301–320. [Google Scholar] [CrossRef]
  15. Zhang, D.X.; Szymura, J.M.; Hewitt, G.M. Evolution and Structural Conservation of the Control Region of Insect Mitochondrial DNA. J. Mol. Evol. 1995, 40, 382–391. [Google Scholar] [CrossRef]
  16. Gibson, R.; Baker, A. Multiple Gene Sequences Resolve Phylogenetic Relationships in the Shorebird Suborder Scolopaci (Aves: Charadriiformes). Mol. Phylogenetics Evol. 2012, 64, 66–72. [Google Scholar] [CrossRef]
  17. MacKinnon, J.; Phillipps, K.; He, F. A Field Guide to the Birds of China; Hunan Education Press: Changsha, China, 2020. [Google Scholar]
  18. Bolger, A.M.; Lohse, M.; Usadel, B. Trimmomatic: A Flexible Trimmer for Illumina Sequence Data. Bioinformatics 2014, 30, 2114–2120. [Google Scholar] [CrossRef]
  19. Jin, J.; Yu, W.; Yang, J.; Song, Y.; dePamphilis, C.W.; Yi, T.; Li, D. GetOrganelle: A Fast and Versatile Toolkit for Accurate de Novo Assembly of Organelle Genomes. Genome Biol. 2020, 21, 241. [Google Scholar] [CrossRef]
  20. Bernt, M.; Donath, A.; Jühling, F.; Externbrink, F.; Florentz, C.; Fritzsch, G.; Pütz, J.; Middendorf, M.; Stadler, P.F. MITOS: Improved de Novo Metazoan Mitochondrial Genome Annotation. Mol. Phylogenetics Evol. 2013, 69, 313–319. [Google Scholar] [CrossRef]
  21. Grant, J.R.; Stothard, P. The CGView Server: A Comparative Genomics Tool for Circular Genomes. Nucleic Acids Res. 2008, 36, W181–W184. [Google Scholar] [CrossRef]
  22. Xiang, C.; Gao, F.; Jakovlić, I.; Lei, H.; Hu, Y.; Zhang, H.; Zou, H.; Wang, G.; Zhang, D. Using PhyloSuite for Molecular Phylogeny and Tree-Based Analyses. IMeta 2023, 2, e87. [Google Scholar] [CrossRef]
  23. Zhang, D.; Gao, F.; Jakovlić, I.; Zou, H.; Zhang, J.; Li, W.X.; Wang, G.T. PhyloSuite: An Integrated and Scalable Desktop Platform for Streamlined Molecular Sequence Data Management and Evolutionary Phylogenetics Studies. Mol. Ecol. Resour. 2020, 20, 348–355. [Google Scholar] [CrossRef]
  24. Perna, N.T.; Kocher, T.D. Patterns of Nucleotide Composition at Fourfold Degenerate Sites of Animal Mitochondrial Genomes. J. Mol. Evol. 1995, 41, 353–358. [Google Scholar] [CrossRef]
  25. Darling, A.C.E.; Mau, B.; Blattner, F.R.; Perna, N.T. Mauve: Multiple Alignment of Conserved Genomic Sequence with Rearrangements. Genome Res. 2004, 14, 1394–1403. [Google Scholar] [CrossRef]
  26. Katoh, K.; Standley, D.M. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. Mol. Biol. Evol. 2013, 30, 772–780. [Google Scholar] [CrossRef]
  27. Ranwez, V.; Douzery, E.J.P.; Cambon, C.; Chantret, N.; Delsuc, F. MACSE v2: Toolkit for the Alignment of Coding Sequences Accounting for Frameshifts and Stop Codons. Mol. Biol. Evol. 2018, 35, 2582–2584. [Google Scholar] [CrossRef]
  28. Kalyaanamoorthy, S.; Minh, B.Q.; Wong, T.K.F.; Von Haeseler, A.; Jermiin, L.S. ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates. Nat. Methods 2017, 14, 587–589. [Google Scholar] [CrossRef]
  29. Ronquist, F.; Teslenko, M.; van der Mark, P.; Ayres, D.L.; Darling, A.; Höhna, S.; Larget, B.; Liu, L.; Suchard, M.A.; Huelsenbeck, J.P. MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice across a Large Model Space. Syst. Biol. 2012, 61, 539–542. [Google Scholar] [CrossRef]
  30. Saitou, N.; Nei, M. The Neighbor-Joining Method: A New Method for Reconstructing Phylogenetic Trees. Mol. Biol. Evol. 1987, 4, 406–425. [Google Scholar] [CrossRef]
  31. Kumar, S.; Stecher, G.; Li, M.; Knyaz, C.; Tamura, K. MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms. Mol. Biol. Evol. 2018, 35, 1547–1549. [Google Scholar] [CrossRef]
  32. Jukes, T.H.; Cantor, C.R. Evolution of Protein Molecules. In Mammalian Protein Metabolism; Munro, H.N., Ed.; Academic Press: New York, NY, USA, 1969; ISBN 978-1-4832-3211-9. [Google Scholar]
  33. Chen, P.; Huan, Z.; Zhu, C.; Han, Y.; Ruan, L. Complete Mitochondrial Genome and Phylogenetic Analysis of Gruiformes and Charadriiformes. Pak. J. Zool. 2020, 52, 425–439. [Google Scholar] [CrossRef]
  34. Gao, Y.; Miao, Y.; Su, X.; Chi, Z.; Yu, Y.; Jiang, F. A Comprehensive Analysis Genome Base on 74 Avian Mitochondrial Compositions. J. Yunnan Agric. Univ. 2009, 24, 51–58. [Google Scholar]
  35. Chen, W.; Zhang, C.; Pan, T.; Liu, W.; Li, K.; Hu, C.; Chang, Q. The Mitochondrial Genome of the Kentish Plover Charadrius Alexandrinus (Charadriiformes: Charadriidae) and Phylogenetic Analysis of Charadrii. Genes Genom. 2018, 40, 955–963. [Google Scholar] [CrossRef]
  36. Zhang, S.; Zheng, X.; Zhou, C.; Yang, K.; Wu, Y. The Complete Mitochondrial Genome of Lesser Sand-Plover Charadrius mongolus atrifrons and Its Phylogenetic Position. Mitochondrial DNA Part B 2021, 6, 2880–2881. [Google Scholar] [CrossRef]
  37. Rand, D.M. The Units of Selection on Mitochondrial DNA. Annu. Rev. Ecol. Syst. 2001, 32, 415–448. [Google Scholar] [CrossRef]
  38. Rousselle, M.; Laverré, A.; Figuet, E.; Nabholz, B.; Galtier, N. Influence of Recombination and GC-Biased Gene Conversion on the Adaptive and Nonadaptive Substitution Rate in Mammals versus Birds. Mol. Biol. Evol. 2019, 36, 458–471. [Google Scholar] [CrossRef]
  39. Lan, G.; Yu, J.; Liu, J.; Zhang, Y.; Ma, R.; Zhou, Y.; Zhu, B.; Wei, W.; Liu, J.; Qi, G. Complete Mitochondrial Genome and Phylogenetic Analysis of Tarsiger indicus (Aves: Passeriformes: Muscicapidae). Genes 2024, 15, 90. [Google Scholar] [CrossRef]
  40. Zhou, X.; Lin, Q.; Fang, W.; Chen, X. The Complete Mitochondrial Genomes of Sixteen Ardeid Birds Revealing the Evolutionary Process of the Gene Rearrangements. BMC Genom. 2014, 15, 573. [Google Scholar] [CrossRef]
  41. Ziomek, K.; Kierzek, E.; Biała, E.; Kierzek, R. The Thermal Stability of RNA Duplexes Containing Modified Base Pairs Placed at Internal and Terminal Positions of the Oligoribonucleotides. Biophys. Chem. 2002, 97, 233–241. [Google Scholar] [CrossRef]
  42. Jühling, F.; Pütz, J.; Bernt, M.; Donath, A.; Middendorf, M.; Florentz, C.; Stadler, P.F. Improved Systematic tRNA Gene Annotation Allows New Insights into the Evolution of Mitochondrial tRNA Structures and into the Mechanisms of Mitochondrial Genome Rearrangements. Nucleic Acids Res. 2012, 40, 2833–2845. [Google Scholar] [CrossRef]
  43. Reyes, A.; Gissi, C.; Pesole, G.; Saccone, C. Asymmetrical Directional Mutation Pressure in the Mitochondrial Genome of Mammals. Mol. Biol. Evol. 1998, 15, 957–966. [Google Scholar] [CrossRef]
  44. Faith, J.J.; Pollock, D.D. Likelihood Analysis of Asymmetrical Mutation Bias Gradients in Vertebrate Mitochondrial Genomes. Genetics 2003, 165, 735–745. [Google Scholar] [CrossRef]
  45. Brown, W.M.; George, M.; Wilson, A.C. Rapid Evolution of Animal Mitochondrial DNA. Proc. Natl. Acad. Sci. USA 1979, 76, 1967–1971. [Google Scholar] [CrossRef]
  46. Mindell, D.P.; Sorenson, M.D.; Dimcheff, D.E. An Extra Nucleotide Is Not Translated in Mitochondrial ND3 of Some Birds and Turtles. Mol. Biol. Evol. 1998, 15, 1568–1571. [Google Scholar] [CrossRef]
  47. Lavrov, D.V.; Pett, W. Animal Mitochondrial DNA as We Do Not Know It: Mt-Genome Organization and Evolution in Nonbilaterian Lineages. Genome Biol. Evol. 2016, 8, 2896–2913. [Google Scholar] [CrossRef]
  48. Ojala, D.; Montoya, J.; Attardi, G. tRNA Punctuation Model of RNA Processing in Human Mitochondria. Nature 1981, 290, 470–474. [Google Scholar] [CrossRef]
  49. Jia, W.; Higgs, P.G. Codon Usage in Mitochondrial Genomes: Distinguishing Context-Dependent Mutation from Translational Selection. Mol. Biol. Evol. 2008, 25, 339–351. [Google Scholar] [CrossRef]
  50. Arab, M.; Höner zu Siederdissen, C.; Tout, K.; Sahyoun, A.H.; Stadler, P.F.; Bernt, M. Accurate Annotation of Protein-Coding Genes in Mitochondrial Genomes. Mol. Phylogenetics Evol. 2017, 106, 209–216. [Google Scholar] [CrossRef]
  51. Harlid, A.; Janke, A.; Arnason, U. The mtDNA Sequence of the Ostrich and the Divergence between Paleognathous and Neognathous Birds. Mol. Biol. Evol. 1997, 14, 754–761. [Google Scholar] [CrossRef] [PubMed]
  52. Parham, J.F.; Feldman, C.R.; Boore, J.L. The Complete Mitochondrial Genome of the Enigmatic Bigheaded Turtle (Platysternon): Description of Unusual Genomic Features and the Reconciliation of Phylogenetic Hypotheses Based on Mitochondrial and Nuclear DNA. BMC Evol. Biol. 2006, 6, 11. [Google Scholar] [CrossRef] [PubMed]
  53. Russell, R.D.; Beckenbach, A.T. Recoding of Translation in Turtle Mitochondrial Genomes: Programmed Frameshift Mutations and Evidence of a Modified Genetic Code. J. Mol. Evol. 2008, 67, 682–695. [Google Scholar] [CrossRef]
  54. Sun, G.; Zhao, C.; Xia, T.; Wei, Q.; Zhang, H. Sequence and Organisation of the Mitochondrial Genome of Japanese Grosbeak (Eophona personata), and the Phylogenetic Relationships of Fringillidae. ZooKeys 2020, 995, 67–80. [Google Scholar] [CrossRef]
  55. Wei, Q.; Wang, X.; Dong, Y.; Shang, Y.; Sun, G.; Wu, X.; Zhao, C.; Sha, W.; Yang, G.; Zhang, H. Analysis of the Complete Mitochondrial Genome of Pteronura brasiliensis and Lontra canadensis. Animals 2023, 13, 3165. [Google Scholar] [CrossRef]
  56. Fourdrilis, S.; de Frias Martins, A.M.; Backeljau, T. Relation between Mitochondrial DNA Hyperdiversity, Mutation Rate and Mitochondrial Genome Evolution in Melarhaphe neritoides (Gastropoda: Littorinidae) and Other Caenogastropoda. Sci. Rep. 2018, 8, 17964. [Google Scholar] [CrossRef]
  57. Watanabe, Y.I.; Suematsu, T.; Ohtsuki, T. Losing the Stem-Loop Structure from Metazoan Mitochondrial tRNAs and Co-Evolution of Interacting Factors. Front. Genet. 2014, 5, 109. [Google Scholar] [CrossRef] [PubMed]
  58. Simpson, R. Splits, Reshuffles and Renaming of the Plovers and Two Thick-Knees. Wader Quest. 2024. Available online: https://www.waderquest.net/2024/02/08/splits-reshuffles-and-renaming-of-the-plovers-and-two-thick-knees/ (accessed on 12 July 2025).
Genes 16 01030 g001
Figure 1. Circular map of the mitogenome of A. veredus. Genes in the outermost circle are transcribed in a clockwise direction, while those in the inner circle are transcribed counterclockwise. The inner circles display GC skew and G + C content.
Figure 1. Circular map of the mitogenome of A. veredus. Genes in the outermost circle are transcribed in a clockwise direction, while those in the inner circle are transcribed counterclockwise. The inner circles display GC skew and G + C content.
Genes 16 01030 g001
Genes 16 01030 g002
Figure 2. Relative synonymous codon usage (RSCU) of A. veredus. The x-axis indicates the amino acids encoded by the respective codons, with each amino acid labeled below. Corresponding RSCU values are plotted on the y-axis.
Figure 2. Relative synonymous codon usage (RSCU) of A. veredus. The x-axis indicates the amino acids encoded by the respective codons, with each amino acid labeled below. Corresponding RSCU values are plotted on the y-axis.
Genes 16 01030 g002
Genes 16 01030 g003
Figure 3. The predicted secondary structures of 22 tRNA genes in the A. veredus mitochondrial genome.
Figure 3. The predicted secondary structures of 22 tRNA genes in the A. veredus mitochondrial genome.
Genes 16 01030 g003
Genes 16 01030 g004
Figure 4. Gene arrangement comparison among the 13 Charadriidae species. The PCGs are represented in the white blocks, the 12S rRNA and 16S rRNA genes are indicated in the red blocks, and the tRNA genes are shown in the green blocks.
Figure 4. Gene arrangement comparison among the 13 Charadriidae species. The PCGs are represented in the white blocks, the 12S rRNA and 16S rRNA genes are indicated in the red blocks, and the tRNA genes are shown in the green blocks.
Genes 16 01030 g004
Genes 16 01030 g005
Figure 5. The ratio of non-synonymous substitutions to synonymous substitutions of PCGs based on 13 Charadriidae mitochondrial genomes.
Figure 5. The ratio of non-synonymous substitutions to synonymous substitutions of PCGs based on 13 Charadriidae mitochondrial genomes.
Genes 16 01030 g005
Genes 16 01030 g006
Figure 6. The NJ and BI phylogenetic tree of 88 Charadriiformes species based on 13 PCGs and 2 rRNA genes. Balearica regulorum in Gruiformes was designated as the outgroup species. The numbers above the branches represent posterior probabilities (BI) and bootstrap support values (NJ), respectively. The families and genera to which the species belong are displayed in colored background boxes. The oriental plover is marked in red.
Figure 6. The NJ and BI phylogenetic tree of 88 Charadriiformes species based on 13 PCGs and 2 rRNA genes. Balearica regulorum in Gruiformes was designated as the outgroup species. The numbers above the branches represent posterior probabilities (BI) and bootstrap support values (NJ), respectively. The families and genera to which the species belong are displayed in colored background boxes. The oriental plover is marked in red.
Genes 16 01030 g006
Table 1. Characteristics of the mitochondrial genome of A. veredus.
Table 1. Characteristics of the mitochondrial genome of A. veredus.
GeneNucleotide PositionsSizes (bp)StrandIntergenic NucleotidesStartStop
tRNAPHE1–7171+---
12s rRNA71–1049979+−1--
tRNAVAL1050–112172+0--
16s rRNA1125–27251601+3--
tRNALEU2718–279174+−8--
ND12794–3771978+2ATGAGG
tRNAILE3772–384170+0--
tRNAGLN3851–392171−9--
tRNAMET3921–398969+−1--
ND23990–50301041+0ATGTAG
tRNATRP5031–509868+0--
tRNAALA5100–516869−1--
tRNAASN5170–524273−1--
tRNACYS5246–531267−3--
tRNATYR5312–538372−−1--
COX15385–69351551+1GTGAGG
tRNASER6927–700074−−9--
tRNAASP7006–707469+5--
COX27076–7759684+1ATGTAA
tRNALYS7761–783070+1--
ATP87832–7999168+1ATGTAA
ATP67990–8673684+−10ATGTAA
COX38673–9456784+−1ATGT
tRNAGLY9457–952569+0--
ND3-CDS19526–9699174+0ATC-
ND3-CDS29701–9877177+1-TAA
tRNAARG9880–994869+2--
ND4L9950–10,246297+1ATGTAA
ND410,240–11,6171378+−7ATGT
tRNAHIS11,618–11,68770+0--
tRNASER11,688–11,75366+0--
tRNALEU11,753–11,82371+−1--
ND511,824–13,6381815+0GTGTAA
CYTB13,651–14,7931143+12ATGTAA
tRNATHR14,798–14,86770+4--
tRNAPRO14,877–14,94670−9--
ND614,969–15,490522−22ATGTAG
tRNAGLU15,494–15,56572−3--
D-loop15,566–16,886
Table 2. Nucleotide composition and AT/GC skew of the A. veredus mitochondrial genome.
Table 2. Nucleotide composition and AT/GC skew of the A. veredus mitochondrial genome.
RegionLength (bp)A%T%G%C%AT%GC%AT SkewGC Skew
Genome16,88631.5124.1913.5330.7755.744.30.131−0.389
PCGs11,39629.4325.8513.2931.4355.2844.720.065−0.406
tRNA154630.0828.0120.8321.0958.0941.910.036−0.006
rRNA258032.9820.8919.1127.0253.8846.120.224−0.171
D-loop132131.7928.6912.4127.1060.4839.520.051−0.372
Table 3. Nucleotide composition of mitochondrial genomes in Charadriidae. Bold Anarhynchus veredus represented the complete mitogenome sequenced in this study.
Table 3. Nucleotide composition of mitochondrial genomes in Charadriidae. Bold Anarhynchus veredus represented the complete mitogenome sequenced in this study.
GenusSpeciesLength (bp)GC Content (%)AT SkewGC Skew
MitogenomePCGsrRNAtRNAMitogenomePCGsrRNAtRNAMitogenomePCGsrRNAtRNAMitogenomePCGsrRNAtRNA
PluvialisP. apricaria15,72311,3882536155145.445.946.141.70.150.0810.220.051−0.402−0.424−0.157−0.002
P. fulva16,85410,2452562155045.24646.541.40.1470.0790.2270.053−0.395−0.413−0.169−0.009
P. squatarola16,86011,3852560154945.846.846.741.60.140.0810.2360.055−0.382−0.415−0.17−0.006
VanellusV. cinereus17,07411,3942578155144.945.345.642.60.1470.0820.2310.047−0.386−0.418−0.194−0.005
V. vanellus16,79511,3912581155144.644.845.842.70.1340.0780.2340.042−0.382−0.41−0.179−0.006
AnarhynchusA. alexandrinus16,90511,3912578155144.845.445.842.50.140.0750.2220.037−0.389−0.409−0.162−0.006
A. atrifrons16,91911,3852580155144.544.945.9420.1530.060.2220.031−0.374−0.403−0.164−0.005
A. leschenaultii16,90511,3882583155344.544.646.342.10.1350.0660.2350.044−0.388−0.403−0.18−0.008
A. mongolus16,84411,3882582154744.744.646.242.20.1310.0670.2350.043−0.388−0.404−0.178−0.009
A. montanus16,94011,3912580154344.845.545.741.80.1370.0720.2160.029−0.381−0.399−0.155−0.008
A. veredus16,88611,3942580154644.344.746.141.90.1310.0650.2240.036−0.389−0.406−0.171−0.006
CharadriusC. dubius15,93311,397256515524545.345.741.50.1390.080.2320.032−0.395−0.406−0.1550.017
C. vociferus16,80811,3912576155044.545.145.241.20.1430.0810.2370.041−0.398−0.418−0.1680.005
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Yuan, B.; Shao, X.; Wang, L.; Yang, J.; Song, X.; Zhong, H. Assembly of Mitochondrial Genome of Oriental Plover (Anarhynchus veredus) and Phylogenetic Relationships Within the Charadriidae. Genes 2025, 16, 1030. https://doi.org/10.3390/genes16091030

AMA Style

Yuan B, Shao X, Wang L, Yang J, Song X, Zhong H. Assembly of Mitochondrial Genome of Oriental Plover (Anarhynchus veredus) and Phylogenetic Relationships Within the Charadriidae. Genes. 2025; 16(9):1030. https://doi.org/10.3390/genes16091030

Chicago/Turabian Style

Yuan, Baodong, Xuan Shao, Lingyi Wang, Jie Yang, Xiaolin Song, and Huaming Zhong. 2025. "Assembly of Mitochondrial Genome of Oriental Plover (Anarhynchus veredus) and Phylogenetic Relationships Within the Charadriidae" Genes 16, no. 9: 1030. https://doi.org/10.3390/genes16091030

APA Style

Yuan, B., Shao, X., Wang, L., Yang, J., Song, X., & Zhong, H. (2025). Assembly of Mitochondrial Genome of Oriental Plover (Anarhynchus veredus) and Phylogenetic Relationships Within the Charadriidae. Genes, 16(9), 1030. https://doi.org/10.3390/genes16091030

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop