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. 2026 Jul 2;16(7):e73888. doi: 10.1002/ece3.73888

Three New Mitochondrial Genomes of Neritidae (Gastropoda, Neritimorpha) From China and Insights Into Their Phylogenetic Position

Yiyong Rao 1, Yuanzheng Meng 2, Sheng Zeng 2, Deyuan Yang 2,✉
PMCID: PMC13327798  PMID: 42396569

ABSTRACT

Marine‐to‐freshwater transitions are frequent in neritid snails. However, phylogenetic relationships among genera remain incompletely resolved, largely because many lineages lack mitogenome data and public records sometimes contain misidentified sequences. Here we assembled complete mitochondrial genomes for three Neritidae species from China—the seagrass specialist Smaragdia rangiana, the brackish‐water Neripteron pileolus, and the brackish‐to‐freshwater Vittina cumingiana—using genome skimming. The mitogenomes range from 15.68 to 15.82 kb, each containing the typical 37 genes and a major non‐coding region. All three mitogenomes are AT‐rich (62.8%–66.0%) with negative AT‐skews and positive GC‐skews. Codon usage analysis revealed that UCU (Serine) exhibits the highest relative synonymous codon usage across all three species, while nucleotide diversity among Neritidae PCGs is highest at third codon positions. Phylogenetic analyses were conducted using multiple datasets (13PCGs123, 13PCGs12, 13PCGsAA, with/without rRNA genes) under maximum likelihood and Bayesian inference, with TreeSpace analysis revealing three distinct topological clusters. All trees recovered the two‐subfamily framework (Neritinae vs. Neritininae). Within Neritininae, S. rangiana clustered with other Smaragdia sequences, N. pileolus grouped with Neripteron violaceum, and V. cumingiana formed a lineage sister to Vitta and Puperita. Several public sequences showed discordant placements consistent with historical synonymy or mislabeling, underscoring the need for voucher‐supported identifications. These new mitogenomes improve taxon sampling for Neritidae and provide a foundation for revisiting habitat transitions with broader genomic data.

Keywords: genome skimming, habitat transitions, mitochondrial genome, Neritidae, phylogeny, sequence curation

This study reports the newly assembled complete mitochondrial genomes for three neritid snails from China: Smaragdia rangiana, Neripteron pileolus, and Vittina cumingiana. Our phylogenetic analyses not only resolved their evolutionary positions within the established two‐subfamily framework but also identified several mislabeled public sequences, highlighting the critical need for voucher‐supported identifications in genomic databases.

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1. Introduction

Neritidae Rafinesque, 1815, commonly known as nerites, is a diverse family of gastropods with approximately 300 extant species (MolluscaBase eds. 2026). Neritids occupy a broad range of habitats, including tropical intertidal shores, mangroves, seagrass beds, and freshwater or brackish streams, and represent an important component of benthic macrofauna (Eichhorst 2016a; Lydeard and Cummings 2019). Habitat use is strongly partitioned within the family: roughly two‐thirds of neritid species are freshwater or brackish, whereas the remainder are marine. This ecological division is broadly reflected in taxonomy. Of the approximately 16 currently recognized genera, only three (Nerita, Mienerita, and Smaragdia) are strictly marine, while the remaining genera are primarily freshwater or brackish‐water dwellers. At the subfamily level, Neritidae is currently divided into two subfamilies, Neritinae Rafinesque, 1815 and Neritininae Poey, 1852. Neritinae contains the marine genera, Nerita and Mienerita, whereas Neritininae comprises the remaining genera, most of which inhabit freshwater or brackish environments (Eichhorst 2016a, 2016b; Bouchet et al. 2017; Lydeard and Cummings 2019).

Neritids show substantial variation in shell morphology, color patterns, life history, and habitat use. This diversity makes them useful model organisms for studying marine–freshwater transitions, adaptive radiation, and intertidal ecology, and also popular among collectors and aquarium hobbyists (Eichhorst 2016a; Ng et al. 2016). The repeated transitions between marine and freshwater environments have attracted particular attention. Holthuis (1995) proposed an evolutionary scenario for Neritidae based on life history and morphology, but this work predates modern taxonomic revisions and should be re‐evaluated within an explicit phylogenetic framework using molecular data.

The taxonomy of Neritidae has undergone repeated revisions at the genus and subfamily levels. Early classifications relied mainly on shell and operculum characters, whereas later systems incorporated radular and reproductive traits; habitat preference has also been used as supporting evidence (Eichhorst 2016a; Lydeard and Cummings 2019). For example, Smaragdia has sometimes been treated as a separate subfamily (Smaragdiinae) because of its distinctive seagrass‐associated ecology, and Septaria was previously elevated to family rank (Septariidae) due to its limpet‐like shell form (Wenz 1938; Golikov and Starobogatov 1975). Many freshwater neritids were historically placed in broad “catch‐all” genera such as Theodoxus or Neritina. Although molecular approaches have improved classification, many taxa still lack sequence data. The widely used modern system of Eichhorst (2016a) recognizes two subfamilies and 16 genera.

Phylogenetic analyses based on a few loci (e.g., cytochrome c oxidase subunit I, 16S rRNA, and ATP synthase subunit alpha) generally support the two‐subfamily framework (Frey and Vermeij 2008; Arquez et al. 2014). However, relationships among genera often remain weakly supported, and single or few markers may fail to capture processes such as introgression or incomplete lineage sorting. Complete mitochondrial genomes (mitogenomes) provide substantially more characters, typically comprising 13 protein‐coding genes, two ribosomal RNA genes, 22 transfer RNA genes, and a major non‐coding region, and have therefore become widely used in gastropod phylogenetics (Boore 1999). Recent neritid studies based on mitogenomes also recover the two‐subfamily split and improve resolution among some genera (Feng et al. 2021; Miao et al. 2022; Qi et al. 2023). Nevertheless, taxon coverage remains incomplete and public databases sometimes include outdated names or misidentified sequences, which can bias downstream phylogenetic inference if not carefully checked (Miao et al. 2022; Qi et al. 2023; Zeng et al. 2025; Lin et al. 2026).

Here, we report the complete mitochondrial genomes of three neritid species from China and assess their phylogenetic placements within Neritidae:

  1. Smaragdia rangiana (Récluz, 1841), a widespread Indo‐Pacific marine species with an emerald‐green shell that lives exclusively on seagrasses. This is the first complete mitogenome reported for the genus Smaragdia.

  2. Neripteron pileolus (Récluz, 1850), a brackish‐water species distributed from Japan to Malaysia that inhabits mangroves and mudflats at river mouths. Because it is frequently confused with Neripteron violaceum (Gmelin, 1791), we discuss potential misidentification issues in public records.

  3. Vittina cumingiana (Récluz, 1842), a brackish‐to‐freshwater species from Southeast Asia commonly found in mangroves and swamps and widely traded in the aquarium hobby. This is the first complete mitogenome reported for the genus Vittina.

2. Materials and Methods

2.1. Specimen Collection, Identification and Sequencing

Specimens were collected from Shanghai and Hainan, China (Figure 1 and Table 1) and identified morphologically following (Eichhorst 2016a, 2016b). No specific permits were required for the collection of these gastropod specimens under Chinese law, as the sampling sites are not located in protected areas and the species collected are neither endangered nor regulated. All collections were conducted in compliance with local regulations. To further confirm taxonomic identity, we conducted BLAST searches against NCBI using assembled mitogenome sequences and reconstructed phylogenetic trees incorporating all available cytochrome c oxidase subunit I and 16S rRNA sequences of Neritidae from NCBI. The detailed BLAST workflow follows Yang et al. (2024). Specimens were fixed in ≥ 99.7% ethanol, stored at −20°C, and deposited at the College of the Environment and Ecology, Xiamen University (voucher numbers: see Table 1).

FIGURE 1.

FIGURE 1

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Specimens used in this study. (A) Smaragdia rangiana (Récluz, 1841), NER‐004; (B) Neripteron pileolus (Récluz, 1850), NER‐037; (C) Vittina cumingiana (Récluz, 1842), NER‐038. The scale bar = 5 mm.

TABLE 1.

Sample information for the three neritid specimens sequenced in this study.

Scientific name Specimen catalog Collection date Locality Latitude Longitude Accession number
Smaragdia rangiana (Récluz, 1841) NER‐004 2024–06 On the seagrass, in a lagoon of Lingshui, Hainan Province, China 18°25′0″ N 110°2′48″ E PX869896
Neripteron pileolus (Récluz, 1850) NER‐037 2024–10 On rocks of the intertidal zone, Nanhui District, Shanghai, China 30°54′24″ N 121°58′24″ E PX869897
Vittina cumingiana (Récluz, 1842) NER‐038 2024–04 Lingshui River, Lingshui, Hainan Province, China 18°30′1″ N 110°4′51″ E PX869898
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Before DNA extraction, specimens were rinsed with ≥ 97% ethanol to minimize potential surface contamination. Foot tissue was dissected to reduce potential gut‐derived contamination. Whole genomic DNA was extracted using the TIANamp Genomic DNA Kit (TIANGEN, Beijing, China). Genome skimming was conducted by Novogene Bioinformatics Technology Co. Ltd. (Beijing, China), using paired‐end 150 bp sequencing on an Illumina NovaSeq X Plus platform. The generated raw sequencing data for each specimen were 3.86 GB (NER‐004), 3.91 GB (NER‐037), and 4.44 GB (NER‐038).

2.2. Assembly and Annotation of Mitochondrial Genome

Raw paired‐end reads were quality‐filtered using fastp v0.23.4 (Chen et al. 2018) to remove adapter sequences and trim low‐quality bases. Mitogenomes were assembled using GetOrganelle v1.7.6.1 (Jin et al. 2020) with multiple k‐mer sizes (17, 21, 33, 39, 45, 55, 65, 75, 85, 95, 105, 115, and 127); all other parameters followed Xu et al. (2024); Yang et al. (2024).

Mitogenomes were annotated using MitoFinder v1.4.1 (Allio et al. 2020) and MitoZ v3.6 (Meng et al. 2019). GenBank‐format annotation files (.gb) were reorganized by custom python script using COX1 as the first gene (Yang et al. 2024). Annotations were then manually curated in Geneious Prime v2022.2.2 (Kearse et al. 2012) following the criteria of Yang et al. (2024).

2.3. Sequence Analyses

Strand asymmetries were calculated using the formulas proposed by Perna and Kocher (1995): AT‐skew = (A − T)/(A + T) and GC‐skew = (G − C)/(G + C). Codon usage and relative synonymous codon usage (RSCU) of the 13 protein‐coding genes (PCGs) were analyzed using PhyloSuite and visualized with the ‘ggplot2’ package (Wickham and Wickham 2016) in R v4.1.3 (R Core Team 2023). Non‐synonymous (Ka) to synonymous (Ks) substitution rate ratios and Nucleotide diversity (Pi) were estimated using DnaSP v.6.0 (Rozas et al. 2017) for all Neritidae sequences listed in Table 2.

TABLE 2.

List of 54 sequences and three outgroups used for phylogenetic analysis.

ID Organism Family Length AT% For TreeSpace
MW694825.1 Clithon corona Neritidae 15,975 64.8
NC_062611.1 Clithon corona Neritidae 15,975 64.8 1
MW694826.1 Clithon lentiginosum Neritidae 15,885 64.8
NC_062610.1 Clithon lentiginosum Neritidae 15,885 64.8 1
MT568501.1 Clithon oualaniense Neritidae 15,706 65.8
NC_068076.1 Clithon oualaniense Neritidae 15,712 65.7 1
KU237287.1 Clithon retropictum Neritidae 15,803 64.9
MG190355.1 Clithon retropictum Neritidae 15,802 64.9
NC_031893.1 Clithon retropictum Neritidae 15,814 64.9 1
MT230542.1 Clithon sowerbianum Neritidae 15,919 64.5
NC_068077.1 Clithon sowerbianum Neritidae 15,895 64.4 1
MW694827.1 Clithon squarrosum Neritidae 15,905 65.0
NC_062613.1 Clithon squarrosum Neritidae 15,905 65.0 1
NC_060871.1 Neritina violacea Neritidae 15,618 65.8 1
MK516738.1 Nerita albicilla Neritidae 15,314 64.5 1
PQ285859.1 Nerita albicilla Neritidae 15,634 64.7
MN477253.1 Nerita balteata Neritidae 15,571 63.3 1
MT161611.1 Nerita chamaeleon Neritidae 15,716 65.8 1
NC_068078.1 Nerita costata Neritidae 15,604 61.6 1
KF728888.1 Nerita fulgurans Neritidae 15,343 64.4 1
NC_068083.1 Nerita histrio Neritidae 15,538 65.5 1
NC_068079.1 Nerita insculpta Neritidae 15,721 61.5 1
MN747116.1 Nerita japonica Neritidae 15,875 65.2 1
LC565707.1 Nerita japonica Neritidae 15,877 65.2
GU810158.1 Nerita melanotragus Neritidae 15,261 63.5 1
NC_068080.1 Nerita ocellata Neritidae 15,577 63.8 1
PQ310099.1 Nerita originalis Neritidae 15,746 64.4 1
OZ373285.1 Nerita plicata Neritidae 16,689 63.5
NC_068081.1 Nerita plicata Neritidae 15,737 61.6 1
NC_068082.1 Nerita reticulata Neritidae 15,630 65.3 1
KF728889.1 Nerita tessellata Neritidae 15,741 64.0 1
MN477254.1 Nerita undata Neritidae 15,583 63.2
NC_087859.1 Nerita undata Neritidae 15,878 62.8 1
KF728890.1 Nerita versicolor Neritidae 15,866 61.6 1
MK395169.1 Nerita yoldii Neritidae 15,719 64.7 1
MW694828.1 Neritina iris Neritidae 15,618 64.3
NC_062612.1 Neritina iris Neritidae 15,618 64.3 1
KY021066.1 Neritina violacea Neritidae 15,710 66.3 1
PP958837.1 Neritona juttingae Neritidae 15,950 62.7 1
MZ315041.1 Septaria lineata Neritidae 15,697 65.8
NC_064130.1 Septaria lineata Neritidae 15,697 65.8 1
KU342667.1 Theodoxus fluviatilis Neritidae 14,122 67.6
MT628587.1 Theodoxus fluviatilis Neritidae 15,667 66.1 1
PX869896 Smaragdia rangiana Neritidae 15,824 62.8 1
PX869897 Neripteron pileolus Neritidae 15,794 66.0 1
PX869898 Vittina cumingiana Neritidae 15,681 63.0 1
KU342665.1 Vitta usnea Neritidae 15,574 64.0 1
SRR1505122 Nerita peloronta Neritidae — —
SRR8318357 “Clithon parvulum” Neritidae — —
SRR19577567 Smaragdia pulcherrima Neritidae — —
SRR8318353 Smaragdia rangiana Neritidae — —
SRR11015441 Neritina pulligera Neritidae — —
SRR8318346 Neritina sp. Neritidae — —
SRR8318350 Puperita pupa Neritidae — —
KU342664.1 Georissa bangueyensis Hydrocenidae 15,267 68.8 1
KU342666.1 Pleuropoma jana Helicinidae 15,851 74.6 1
KU342669.1 Titiscania limacina Neritopsidae 15,046 61.8 1
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2.4. Phylogenetic Analysis

We downloaded all publicly available Neritidae mitogenome records from the NCBI Nucleotide/GenBank database (62 accessions available as of 1 January 2026). Because redundancy can occur in GenBank (e.g., identical or near‐identical mitogenome sequences deposited under different accession numbers), we dereplicated the dataset in PhyloSuite and retained unique sequences. After filtering, 44 non‐redundant mitogenomes were kept for downstream analyses. To ensure consistent annotation criteria and to correct potential errors in database records, we re‐annotated all mitogenomes using the workflow described above (see also Yang et al. 2024).

To increase taxon sampling, we additionally retrieved publicly available Neritidae transcriptome datasets from the NCBI Sequence Read Archive (SRA) and extracted mitochondrial genes following the pipeline described by Zeng et al. (2025). Briefly, the target mitochondrial genes were annotated and extracted from the transcriptomic data using MitoFinder v1.4 (Allio et al. 2020). Complete mitochondrial genomes were not obtained from these datasets; instead, we successfully assembled and retrieved all 13 protein‐coding genes (PCGs) and the two ribosomal RNAs (12S and 16S). Our preliminary phylogenetic analyses based on the 13PCGs + 2rRNA dataset demonstrated that sequences belonging to the same species formed monophyletic groups (Data S2). Therefore, to minimize sequence redundancy and streamline the phylogenetic dataset, we selected a single representative sequence for each species for the final analyses.

Ultimately, we analyzed two datasets: (1) a combined dataset including mitogenomes and transcriptome‐derived mitochondrial genes (“mitogenomes + RNA”); and (2) a mitogenome‐only dataset (“mitogenomes”).

For the mitogenome‐only dataset, we constructed several alignments to evaluate sensitivity to coding position and partitioning: (i) 13PCGs123, all codon positions of the 13 protein‐coding genes; (ii) 13PCGs123 + 2rRNA, 13PCGs123 plus the two rRNA genes; (iii) 13PCGs12, first and second codon positions of the 13 protein‐coding genes; (iv) 13PCGs12 + 2rRNA, 13PCGs12 plus the two rRNA genes; (v) 13PCGsAA, amino acid translations of the 13 protein‐coding genes; (vi) 13PCGs‐np, 13 protein‐coding genes without codon partitioning; and (vii) 13PCGs + 2rRNA‐np, 13 protein‐coding genes plus the two rRNA genes without partitioning. Three Cycloneritida taxa, Titiscania limacina (KU342669, Neritopsidae), Georissa bangueyensis (KU342664, Hydrocenidae), and Pleuropoma jana (KU342666, Helicinidae) were used as outgroups (Qi et al. 2023).

TrimAl v1.2 (Capella‐Gutiérrez et al. 2009) was employed to remove ambiguously aligned regions using the ‘automated1’ setting (Data S1 and Table S1). Substitution models were selected using ModelFinder v2.2.0 (Kalyaanamoorthy et al. 2017) based on the Bayesian Information Criterion (BIC) for maximum likelihood (ML) analysis and the corrected Akaike Information Criterion (AICc) for Bayesian inference (BI) analysis under a partitioned model (Data S1 and Table S2). ML phylogenies were performed using IQ‐TREE v2.2.2 (Nguyen et al. 2015; Kalyaanamoorthy et al. 2017) with the best partition scheme and an edge‐linked partition model. Node support was evaluated with 100,000 ultrafast bootstraps. BI phylogenies were constructed in MrBayes v3.2.7a (Ronquist et al. 2012), with two parallel runs and 2000, 000 generations. Convergence was assessed by the average standard deviation of split frequencies (ASDSF), with additional generations added if the ASDSF value exceeded 0.005.

Topological discrepancies between the resulting trees were evaluated using TreeSpace (Jombart et al. 2017) in R v4.3.1 (R Core Team 2023), which employs Metric Multidimensional Scaling (MDS) to visualize tree relationships and hierarchical clustering methods (including single linkage, complete linkage, UPGMA, and Ward's method) to formally identify distinct phylogenetic clusters. Finally, phylogenetic trees were visualized and edited using iTOL v6 (Letunic and Bork 2024).

3. Results

3.1. Species Identification

Species identity was assessed using both morphology and mitochondrial markers (cytochrome c oxidase subunit I and 16S rRNA; Data S1 and Table S3). Live individuals were identified morphologically following Eichhorst (2016a, 2016b) (Figure 1) and further validated by BLAST searches and marker‐based phylogenies.

Smaragdia rangiana (Récluz, 1841), NER‐004 (Figure 1A): Shell small, thin, elongated semi‐globose. Surface smooth. Spire prominent. Three whorls, and the body whorl is greatly expanded. Parietal shelf convex and very swollen, cream color with green tints. Columella fairly straight with five to six teeth. Shell yellowish‐green (bright green when alive), with up to five lines of white blotches or bars, and each white blotch has a black line on the leading edge. Distinguished by distribution (Indo‐Pacific) from S. viridis (tropical Atlantic). Molecular validation via phylogenetic analysis, using mitochondrial genome sequences assembled from publicly available transcriptome data (SRR8318353), supported the morphological identification (Data S1 and Table S3).

Neripteron pileolus (Récluz, 1850), NER‐037 (Figure 1B): Shell medium size, solid, elongated ovate. Final whorl flared into an oval base with a sharp lip that extends completely 360° around the base. Spire curved in on itself, extended beyond the parietal shelf. Surface always eroded, with apparent axial growth lines. Parietal shelf slightly concave, smooth. Aperture and parietal shelf cream color with bluish‐gray staining. A long, shallow indentation on the columella, with 10–25 small teeth. Shell greenish or yellowish brown, irregular zigzag lines forming tent or flame patterns. Distinguished by a bluish‐gray parietal shelf from N. violacea (red) and N. cornucopia (black). Molecular validation showed high identity (over 99% of COI, 16S, and mtgenome) to Neritina violacea sequences, but Lin et al. (2026) mentioned that some records labeled as N. violacea are actually Neripteron pileolus (Data S1 and Table S3).

Vittina cumingiana (Récluz, 1842), NER‐038 (Figure 1C): Shell medium size, elongated ovate. Surface glossy and smooth. Spire high and prominent. Apex eroded, with about three whorls left. Parietal shelf convex, swollen, with leather‐like microscopic texture; cream to peach or orange color. A central depression on the columella with 7–10 teeth. Shell black, with a series of thin, parallel, zigzag, yellow spiral stripes. Distinguished by narrow spiral stripes from V. turrita (with broad spiral stripes) and by a high spire from other similar congeners (with moderate spires). Molecular validation supported assignment to the genus Vittina (Data S1 and Table S3).

3.2. Mitogenome Organization

We assembled complete mitogenomes for three species: Smaragdia rangiana (15,824 bp; NER‐004; PX869896), Neripteron pileolus (15,794 bp; NER‐037; PX869897), and Vittina cumingiana (15,681 bp; NER‐038; PX869898) (Figure 2). Consistent with previously reported Neritidae mitogenomes, the structural characteristics of these three newly sequenced genomes are strictly conserved. Each mitogenome contained the typical set of 37 genes (including 13 protein‐coding genes and two rRNAs) and a major non‐coding region (Table 3), exhibiting no gene rearrangements (Lin et al. 2026). The overall A + T content was 62.8% in S. rangiana, 66.0% in N. pileolus, and 63.0% in V. cumingiana (Table 4), falling within the range reported for other neritid mitogenomes (Table 2).

FIGURE 2.

FIGURE 2

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Gene maps of the Smaragdia rangiana (NER‐004), Neripteron pileolus (NER‐037), and Vittina cumingiana (NER‐038) mitogenomes. The innermost and middle circles depict the distribution of the sequencing depth, GC content, and GC‐skew, respectively. The outermost circle represents the arrangement of genes: outer genes from the forward strand, and inner genes from the reverse strand.

TABLE 3.

Features of three species' mitogenomes (S. rangiana/N. pileolus/V. cumingiana).

Genes Position Size Intergenic nucleotides Codon Strand
From To Start Stop
COX1 1/1/1 1548/1548/1548 1548/1548/1548 11/11/11 ATG/ATG/ATG TAA/TAA/TAA H/H/H
COX2 1560/1560/1560 2249/2249/2249 690/690/690 1/1/1 ATG/ATG/ATG TAA/TAG/TAA H/H/H
trnD(guc) 2251/2251/2251 2316/2316/2316 66/66/66 0/0/0 H/H/H
ATP8 2317/2317/2317 2481/2481/2481 165/165/165 5/6/6 ATG/ATG/ATG TAA/TAA/TAA H/H/H
ATP6 2487/2488/2488 3188/3189/3189 702/702/702 22/22/22 ATG/ATG/ATG TAA/TAA/TAA H/H/H
trnF(gaa) 3211/3212/3212 3278/3279/3279 68/68/68 9/9/9 L/L/L
ND5 3288/3289/3289 4992/4993/4993 1705/1705/1705 0/0/0 ATG/ATG/ATG T/T/T L/L/L
trnH(gug) 4993/4994/4994 5058/5059/5059 66/66/66 9/9/9 L/L/L
ND4 5068/5069/5069 6424/6425/6425 1357/1357/1357 −7/−7/−7 ATG/ATG/ATG T/T/T L/L/L
ND4L 6418/6419/6419 6711/6712/6712 294/294/294 4/4/4 ATG/ATG/ATG TAA/TAA/TAA L/L/L
trnT(ugu) 6716/6717/6717 6783/6784/6784 68/68/68 3/5/6 H/H/H
trnS(uga) 6787/6790/6791 6851/6854/6855 65/65/65 5/5/5 L/L/L
CYTB 6857/6860/6861 7993/7996/7997 1137/1137/1137 5/10/11 ATG/ATG/ATG TAA/TAA/TAA L/L/L
ND6 7999/8007/8009 8505/8513/8515 507/507/507 1/1/1 ATG/ATG/ATG TAA/TAA/TAA L/L/L
trnP(ugg) 8507/8515/8517 8572/8580/8582 66/66/66 1/0/1 L/L/L
ND1 8574/8581/8584 9506/9513/9516 933/933/933 0/0/0 ATG/ATG/ATG TAG/TAA/TAA L/L/L
trnL(uaa) 9507/9514/9517 9574/9581/9584 68/68/68 0/0/0 L/L/L
trnL(uag) 9575/9582/9585 9644/9650/9654 70/69/70 0/0/0 L/L/L
l‐rRNA 9645/9651/9655 10,943/10949/10954 1299/1299/1300 0/0/0 L/L/L
trnV(uac) 10,944/10950/10955 11,010/11017/11022 67/68/68 0/0/0 L/L/L
s‐rRNA 11,011/11018/11023 11,867/11879/11886 857/862/864 0/0/0 L/L/L
trnM(cau) 11,868/11880/11887 11,934/11946/11953 67/67/67 2/5/4 L/L/L
trnY(gua) 11,937/11952/11958 12,004/12019/12025 68/68/68 7/5/5 L/L/L
trnC(gca) 12,012/12025/12031 12,075/12089/12094 64/65/64 0/0/0 L/L/L
trnW(uca) 12,076/12090/12095 12,142/12155/12160 67/66/66 0/0/0 L/L/L
trnQ(uug) 12,143/12156/12161 12,211/12224/12229 69/69/69 0/0/0 L/L/L
trnG(ucc) 12,212/12225/12230 12,276/12289/12295 65/65/66 2/6/1 L/L/L
trnE(uuc) 12,279/12296/12297 12,344/12361/12362 66/66/66 773/683/580 L/L/L
COX3 13,118/13045/12943 13,897/13824/13722 780/780/780 28/39/31 ATG/ATG/ATG TAA/TAA/TAA H/H/H
trnK(uuu) 13,926/13864/13754 13,991/13930/13820 66/67/67 10/11/16 H/H/H
trnA(ugc) 14,002/13942/13837 14,069/14009/13904 68/68/68 3/8/14 H/H/H
trnR(ucg) 14,073/14018/13919 14,141/14086/13987 69/69/69 9/14/12 H/H/H
trnN(guu) 14,151/14101/14000 14,223/14172/14071 73/72/72 4/26/12 H/H/H
trnI(gau) 14,228/14199/14084 14,296/14267/14152 69/69/69 0/0/0 H/H/H
ND3 14,297/14268/14153 14,650/14621/14506 354/354/354 4/3/5 ATG/ATG/ATG TAA/TAA/TAG H/H/H
trnS(gcu) 14,655/14625/14512 14,721/14692/14579 67/68/68 1/0/0 H/H/H
ND2 14,723/14693/14580 15,824/15794/15681 1102/1102/1102 0/0/0 ATG/ATG/ATG T/T/T H/H/H
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TABLE 4.

Composition and skewness of three species' mitogenomes (S. rangiana/ N. pileolus/ V. cumingiana).

Regions Size (bp) T(U) C A G AT (%) GC (%) GT (%) AT skewness GC skewness
Full genome 15,824/15794/15681 32.2/34.6/32.8 16.7/14.4/16 30.6/31.4/30.2 20.5/19.6/21 62.8/66/63 37.2/34/37 52.7/54.2/53.8 −0.026/−0.049/−0.04 0.101/0.152/0.135
PCGs 11,271/11271/11271 37.3/38.7/37.2 19.1/17.2/19 24.1/26.7/24.9 19.5/17.5/19 61.4/65.4/62.1 38.6/34.7/38 56.8/56.2/56.2 −0.214/−0.184/−0.198 0.011/0.009/0.002
tRNAs 1482/1483/1484 31.6/32.6/32.4 15.4/14.9/15.1 30.7/30.5/30.4 22.3/21.9/22.1 62.3/63.1/62.8 37.7/36.8/37.2 53.9/54.5/54.5 −0.015/−0.033/−0.032 0.183/0.19/0.188
rRNAs 2156/2161/2164 29.4/32.2/30.9 16.8/15.5/16.4 35.6/35.5/34.8 18.2/16.8/17.9 65/67.7/65.7 35/32.3/34.3 47.6/49/48.8 0.096/0.049/0.059 0.04/0.043/0.043
1st codon position 3757/3757/3757 29.8/30.7/30.3 17.9/16.9/17.5 25.6/26.1/25.5 26.7/26.2/26.7 55.4/56.8/55.8 44.6/43.1/44.2 56.5/56.9/57 −0.077/−0.082/−0.086 0.196/0.216/0.208
2nd codon position 3757/3757/3757 43/43/43.3 22.7/22.4/22.2 18/18.2/18 16.4/16.5/16.5 61/61.2/61.3 39.1/38.9/38.7 59.4/59.5/59.8 −0.411/−0.406/−0.413 −0.161/−0.151/−0.146
3rd codon position 3757/3757/3757 39.1/42.3/37.9 16.6/12.2/17.2 28.9/35.7/31.1 15.4/9.7/13.8 68/78/69 32/21.9/31 54.5/52/51.7 −0.15/−0.084/−0.098 −0.039/−0.114/−0.107
ATP6 702/702/702 39.5/43.3/39.9 17.2/14.7/18.2 22.1/22.4/21.5 21.2/19.7/20.4 61.6/65.7/61.4 38.4/34.4/38.6 60.7/63/60.3 −0.282/−0.319/−0.299 0.104/0.145/0.055
ATP8 165/165/165 39.4/41.2/41.2 12.7/10.3/10.9 28.5/30.9/30.3 19.4/17.6/17.6 67.9/72.1/71.5 32.1/27.9/28.5 58.8/58.8/58.8 −0.161/−0.143/−0.153 0.208/0.261/0.234
COX1 1548/1548/1548 37.6/40.4/38.8 18.1/15.3/16 22.9/23/23 21.4/21.3/22.2 60.5/63.4/61.8 39.5/36.6/38.2 59/61.7/61 −0.242/−0.275/−0.256 0.083/0.163/0.161
COX2 690/690/690 35.4/36.4/35.5 17.4/14.5/16.1 26.4/28.4/27.7 20.9/20.7/20.7 61.8/64.8/63.2 38.3/35.2/36.8 56.3/57.1/56.2 −0.146/−0.123/−0.124 0.091/0.177/0.126
COX3 780/780/780 36.9/38.8/38.1 18.7/16.2/17.1 20.6/22.4/21.4 23.7/22.6/23.5 57.5/61.2/59.5 42.4/38.8/40.6 60.6/61.4/61.6 −0.283/−0.268/−0.28 0.118/0.166/0.158
CYTB 1137/1137/1137 35.4/36.7/36.1 22/20.3/22.1 24.9/27.8/25.1 17.8/15.2/16.7 60.3/64.5/61.2 39.8/35.5/38.8 53.2/51.9/52.8 −0.174/−0.138/−0.181 −0.106/−0.144/−0.138
ND1 933/933/933 36.5/37.2/37 20.5/19.2/19.2 23.5/27/25.4 19.5/16.6/18.4 60/64.2/62.4 40/35.8/37.6 56/53.8/55.4 −0.218/−0.159/−0.186 −0.024/−0.072/−0.02
ND2 1102/1102/1102 38.9/43.3/39.8 13.8/10.6/13.2 22.6/24.2/22.1 24.7/21.9/24.9 61.5/67.5/61.9 38.5/32.5/38.1 63.6/65.2/64.7 −0.265/−0.282/−0.286 0.283/0.346/0.308
ND3 354/354/354 40.1/44.4/41.5 13.6/10.7/13 20.1/19.8/20.3 26.3/25.1/25.1 60.2/64.2/61.8 39.9/35.8/38.1 66.4/69.5/66.6 −0.333/−0.383/−0.342 0.319/0.402/0.319
ND4 1357/1357/1357 38.7/37.2/35.5 20.9/21.4/23.7 24.8/29.3/26.9 15.5/12.1/13.9 63.5/66.5/62.4 36.4/33.5/37.6 54.2/49.3/49.4 −0.218/−0.118/−0.138 −0.147/−0.278/−0.263
ND4L 294/294/294 34.7/34.4/31.3 19.4/18.4/21.8 28.9/30.3/29.3 17/17/17.7 63.6/64.7/60.6 36.4/35.4/39.5 51.7/51.4/49 −0.091/−0.063/−0.034 −0.065/−0.038/−0.103
ND5 1705/1705/1705 35.9/35.4/34.8 22.7/20.9/22.8 26.1/31/27.3 15.3/12.7/15 62/66.4/62.1 38/33.6/37.8 51.2/48.1/49.8 −0.158/−0.067/−0.121 −0.194/−0.243/−0.206
ND6 507/507/507 39.4/40/37.5 18.1/17.2/20.1 26/29.6/26 16.4/13.2/16.4 65.4/69.6/63.5 34.5/30.4/36.5 55.8/53.2/53.9 −0.205/−0.15/−0.18 −0.051/−0.13/−0.103
l‐rRNA 1299/1299/1300 29.2/33.3/32 17.2/15.5/16.4 36.4/35.6/34.8 17.2/15.6/16.8 65.6/68.9/66.8 34.4/31.1/33.2 46.4/48.9/48.8 0.11/0.033/0.043 −0.002/0.002/0.012
s‐rRNA 857/862/864 29.6/30.5/29.3 16.2/15.4/16.4 34.3/35.3/34.7 19.8/18.8/19.6 63.9/65.8/64 36/34.2/36 49.4/49.3/48.9 0.073/0.072/0.085 0.1/0.098/0.087
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When calculated from the coding strand of individual genes, the A + T content of the 13 protein‐coding genes was 61.4% (S. rangiana), 65.4% (N. pileolus), and 62.1% (V. cumingiana) (Table 4). Among the protein‐coding genes (PCGs), ATP8 exhibited the highest A + T content, ranging from 67.9% to 72.1% across the three species (S. rangiana: 67.9%; N. pileolus: 72.1%; V. cumingiana: 71.5%), while COX3 displayed the lowest, varying from 57.5% to 61.2% (S. rangiana: 57.5%; N. pileolus: 61.2%; V. cumingiana: 59.5%) (Table 3).

AT‐skew values were negative across all three species, whereas GC‐skew values were positive. AT‐skew values followed the pattern: −0.026 (S. rangiana) > −0.040 (V. cumingiana) > −0.049 (N. pileolus). GC‐skew values demonstrated the order: 0.152 (N. pileolus) > 0.135 (V. cumingiana) > 0.101 (S. rangiana) (Table 4).

3.3. Genes and Codon Usage

Among the 13 protein‐coding genes, all utilized the standard initiation codon ATG (Table 3). All 13 genes terminated with canonical stop codons (TAG, TAA, and T). Transfer RNA gene lengths varied from 64 to 73 bp. The 16S rRNA gene length was 1299 bp (S. rangiana and V. cumingiana) and 1300 bp (N. pileolus), while the 12S rRNA gene was 857 bp (S. rangiana), 862 bp (V. cumingiana), and 864 bp (N. pileolus) (Table 3). The non‐coding region (NCR), located between trnE and COX3, was 780 bp in three mitogenomes.

Relative synonymous codon usage (RSCU) analysis revealed that UCU (S) exhibited the highest RSCU values across all three species: 2.61 (S. rangiana), 2.55 (V. cumingiana), and 2.18 (N. pileolus). The lowest RSCU values were observed for CCG (P) in S. rangiana (0.22), V. cumingiana (0.05), and N. pileolus (0.19) (Figure 3, Data S1 and Table S4).

FIGURE 3.

FIGURE 3

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Relative synonymous codon usage (RSCU) of the three mitogenomes. The codon families are provided under the x‐axis. The frequency of amino acid usage is listed above the column.

3.4. Nucleotide Diversity and Evolutionary Rate Analysis

Nucleotide diversity (Pi) of the analyzed genes ranged from 0.144 to 0.234. Sequence variability was lowest in COX1 (Pi = 0.144), COX2 (0.150), ATP6 (0.173), and COX3 (0.186), and highest in ND6 (0.234), ND2 (0.216), and ND4 (0.211). Non‐synonymous to synonymous substitution ratio (Ka/Ks) analysis revealed that all genes are under purifying selection (Ka/Ks < 1). Evolutionary rates were comparatively slow for COX1 (Ka/Ks = 0.024), CYTB (0.030), ND1 (0.032), and ATP6 (0.034), but relatively fast for ATP8 (0.122), ND2 (0.070), and ND6 (0.069) (Figure 4).

FIGURE 4.

FIGURE 4

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Nucleotide diversity and Ka/Ks rates of 13 PCGs based on Neritidae sequences. The light purple, pink, and light yellow columns represent the values of Ks, Ka, and Ka/Ks, respectively. The red dot represents the value of nucleotide diversity (Pi).

3.5. Phylogenetic Analysis

The gene arrangement of the 13 PCGs and 2 rRNAs within the family Neritidae is completely consistent (Lin et al. 2026) and cannot provide useful phylogenetic information. A total of 10 ML and BI trees were inferred from five mitogenome datasets of Neritidae. These 10 trees were grouped into three clusters, representing three distinct tree types (see Figure 5B–E). As illustrated in Figure 5B, the choice of the dataset exerted a more substantial effect on the resulting tree topology than the choice of phylogenetic inference method. The most common topology, Cluster 1, is shown in Figure 5C. An extra phylogenetic tree including more mitogenome sequences and mitogenome sequences assembled from transcriptome data was chosen as the main figure (Figure 5A). The structure of three clusters is generally consistent, except the position of outgroup sequence Georissa bangueyensis (KU342664) is different in Cluster 2, and Nerita melanotragus (GU810158) is different in Cluster 3.

FIGURE 5.

FIGURE 5

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Maximum likelihood (ML) and Bayesian inference (BI) tree of Neritidae based on the “mitogenomes + RNA” dataset (A) and treespace analysis of phylogenies from seven “mitogenome” datasets (B–E). The GenBank accession numbers used are listed after the species names. The scale bar (0.1) corresponds to the estimated number of substitutions per site. Numbers at nodes are statistical support values for “BI posterior probabilities/ML bootstrap support”. “Unlabeled” denotes 100% bootstrap support. Color‐coded clades are different genera within Neritidae. (B) Two‐dimensional MDS plot of 10 trees, colored by different clusters. (C–E) For each cluster identified in B, a representative tree was selected.

The phylogenetic tree included representatives from 12 genera of Neritidae (Figure 5A) and recovered two primary clades. Clade A comprised the marine genus Nerita, whereas Clade B contained the remaining sampled genera (Theodoxus, Neritona, Smaragdia, Neritina, Septaria, Neripteron, Vittina, Vitta, Puperita, Clithon, and one undetermined lineage). All three newly assembled mitogenomes fell within Clade B. Smaragdia rangiana (NER‐004) clustered with another S. rangiana mitogenome assembled from transcriptome data (SRR8318353) and with an additional Smaragdia sequence; a transcriptome‐derived sequence labeled as “Clithon parvulum” (SRR8318357) was placed within this clade. Neripteron pileolus (NER‐037) clustered with a record labeled as “Neritina violacea” (NC_060871) and with Neripteron violaceum (KY021066). Vittina cumingiana (NER‐038) formed a distinct lineage sister to Vitta and Puperita.

4. Discussion

Our phylogenetic analyses support the division of Neritidae into two subfamilies, Neritinae and Neritininae, consistent with previous mitogenome‐based studies (Feng et al. 2021; Miao et al. 2022; Qi et al. 2023; Lin et al. 2026). Clade A (Figure 5) contained only the marine genus Nerita and corresponds to Neritinae. Clade B comprised genera of Neritininae, most of which inhabit freshwater or brackish environments and often show amphidromous life histories (Ford 1979; Eichhorst 2016a, 2016b).

Phylogenetic relationships were generally stable across datasets and inference methods, with a few exceptions (e.g., the placement of Nerita melanotragus [GU810158] and the outgroup Georissa bangueyensis [KU342664]). Mitochondrial gene order was highly conserved across Neritidae and therefore provided little additional phylogenetic signal. This conservation, together with limited taxon sampling for several genera, suggests that mitogenomes alone may be insufficient to fully resolve relationships within the family. Moreover, current trees remain inadequate for testing links between habitat shifts and diversification in Neritidae. The three species involved in this study generally share similar habitats with their congeners: S. rangiana is marine, N. pileolous is brackish, and V. cumingiana is freshwater and brackish. Notably, Smaragdia is the only completely marine genus in the Neritininae clade, which may suggest a secondary transition from freshwater/brackish to marine habitat. However, this transformation may not have occurred only a few times. Holthuis (1995) suggested at least 12 transitions among marine, brackish, and freshwater habitats within Cycloneritida, and Qi et al. (2023) also inferred repeated habitat transitions. Broader taxon sampling and integration of nuclear genomic data will be required to robustly reconstruct the evolutionary history of all 16 neritid genera.

All three newly assembled mitogenomes belonged to Clade B. Smaragdia rangiana (NER‐004) clustered with other Smaragdia sequences and with a transcriptome‐derived record labeled as “Clithon parvulum” (SRR8318357), whereas other Clithon species formed a separate monophyletic group. This pattern suggests that SRR8318357 may be mislabeled. Similarly, Neripteron pileolus (NER‐037) clustered most closely with a record labeled as “Neritina violacea” (NC_060871, a junior synonym of Neripteron violaceum) rather than with the authenticated N. violaceum sequence (KY021066), again suggesting potential misidentification or the use of historical synonyms. Vittina cumingiana (NER‐038) represents the first available mitogenome for Vittina; additional sampling will be needed to test the monophyly and internal relationships of this genus.

In our phylogenetic analyses, the outgroup Georissa bangueyensis (Hydrocenidae) showed unstable placement across different datasets, clustering inconsistently in TreeSpace analysis (Cluster 2, Figure 5B). This instability, together with the considerable phylogenetic distance between Hydrocenidae and Neritidae, raises the possibility of long‐branch attraction (LBA) artifacts (Bergsten 2005). Ideally, a more closely related outgroup within Neritimorpha (e.g., Phenacolepadidae or a broader representation of Neritopsidae) would be used to root the tree. However, complete mitogenomes for these families are currently unavailable in public databases. We encourage future studies to include additional neritimorph mitogenomes to mitigate potential LBA effects.

Voucher metadata for “Clithon parvulum” (SRR8318357; voucher MCZ:Mala:386153) indicate collection from seagrass blades (Harvard University and Morris 2026), a typical habitat of Smaragdia, whereas Clithon parvulum is generally reported from freshwater streams. Notably, Smaragdia paulucciana (Gassies, 1870) is a junior synonym of Clithon parvulum (Le Guillou, 1841) (Eichhorst 2016b; MolluscaBase eds. 2026). Eichhorst (2016b) further noted that the name S. paulucciana has been inconsistently applied and in some cases refers to a distinct species, Smaragdia patburkeae Eichhorst, 2016. Together, these observations suggest that MCZ:Mala:386153 may represent a misidentified specimen of Smaragdia. Unfortunately, the voucher record lacks photographs, and the shell was broken for soft tissue extraction, preventing re‐examination. A similar problem may occur in the Neripteron clade. Neripteron violaceum (often listed under its synonym Neritina violacea) and N. pileolus have been confused in the literature. For example, Tchang et al. (1964) described Neritina violacea with traits consistent with N. pileolus (yellow‐brown shell, bluish‐gray aperture and parietal shelf, and irregular zigzag patterns), whereas Li (2019) illustrated a typical N. violaceum specimen under the name N. pileolus. Because the NCBI record NC_060871 lacks locality, voucher information, and images, we can only infer its identity indirectly from molecular placement. Ideally, definitive confirmation of these cases would require re‐examination of the original vouchers. However, the voucher for SRR8318357 (MCZ:Mala:386153) was dissected and is no longer intact (Harvard University and Morris 2026), and NC_060871 lacks any voucher information in its GenBank record. Therefore, we present the classification corrections suggested in this paper only as provisional recommendations, warranting future testing with newly collected, well‐vouchered specimens accompanied by accessible images and locality data. For other species labeled as their synonyms in the database mentioned by Lin et al. (2026), we verified them using MolluscaBase (MolluscaBase eds. 2026).

After excluding apparently mislabeled records from Smaragdia, Neripteron, and Neritina, the genera sampled in this study were recovered as monophyletic. This emphasizes that careful verification of species identifications is essential for mitogenome‐based phylogenetics. We recommend that future submissions to public databases include voucher information, clear specimen images, and key diagnostic characters to support downstream comparative and phylogenetic analyses.

Author Contributions

Yiyong Rao: data curation (equal), funding acquisition (lead), visualization (equal), writing – original draft (equal), writing – review and editing (equal). Yuanzheng Meng: methodology (equal), writing – original draft (equal), writing – review and editing (equal). Sheng Zeng: formal analysis (equal), visualization (equal), writing – original draft (equal), writing – review and editing (equal). Deyuan Yang: conceptualization (lead), data curation (equal), formal analysis (equal), investigation (lead), methodology (equal), project administration (lead), supervision (lead), writing – original draft (equal), writing – review and editing (equal).

Funding

This work was supported by the National Natural Science Foundation of China (42206119) and the Central Public‐Interest Scientific Institution Basal Research Fund, South China Sea Fisheries Research Institute, CAFS (2024RC08).

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Table S1: Original and TrimAl lengths of 13 PCGs, 2 rRNAs, and 13 PCGsAA sequences.

Table S2: Best partitioning schemes and models based on different datasets for maximum likelihood and Bayesian inference analysis.

Table S3: The Blast results of mtgenome, COX1 and 16S (Top 10 blast results are shown).

Table S4: Codon numbers and relative synonymous codon usage (RSCU) of 13 PCGs in three mitogenomes.

ECE3-16-e73888-s001.xlsx (34.9KB, xlsx)

Data S2: Preliminary Maximum Likelihood (ML) and Bayesian Inference (BI) phylogenetic trees of Neritidae based on the 13PCGs + 2rRNA dataset.

ECE3-16-e73888-s002.pdf (433.3KB, pdf)

Acknowledgments

We thank the editor and two anonymous reviewers for their constructive comments, which greatly improved the quality of the manuscript. We also thank Mr. Xiang Guo and Zun‐Yi Shen for providing specimens.

Data Availability Statement

The data generated in this study have been deposited as follows: the complete mitochondrial genomes in NCBI GenBank under the accession numbers PX869896 for Smaragdia rangiana, PX869897 for Neripteron pileolus, and PX869898 for Vittina cumingiana.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1: Original and TrimAl lengths of 13 PCGs, 2 rRNAs, and 13 PCGsAA sequences.

Table S2: Best partitioning schemes and models based on different datasets for maximum likelihood and Bayesian inference analysis.

Table S3: The Blast results of mtgenome, COX1 and 16S (Top 10 blast results are shown).

Table S4: Codon numbers and relative synonymous codon usage (RSCU) of 13 PCGs in three mitogenomes.

ECE3-16-e73888-s001.xlsx (34.9KB, xlsx)

Data S2: Preliminary Maximum Likelihood (ML) and Bayesian Inference (BI) phylogenetic trees of Neritidae based on the 13PCGs + 2rRNA dataset.

ECE3-16-e73888-s002.pdf (433.3KB, pdf)

Data Availability Statement

The data generated in this study have been deposited as follows: the complete mitochondrial genomes in NCBI GenBank under the accession numbers PX869896 for Smaragdia rangiana, PX869897 for Neripteron pileolus, and PX869898 for Vittina cumingiana.

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