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16 December 2025

DNA Barcode Identification for Gastropod and Bivalve Species in Coastal Bays and Islands of Vietnam

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Institute of Chemistry, Vietnam Academy of Science and Technology (VAST), 18 Hoang Quoc Viet, Nghia Do, Hanoi 10000, Vietnam
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VNTEST Institute for Quality Testing and Inspection, Lot DM10-1 Small Industry Cluster, Van Phuc Silk Village, Ha Dong, Hanoi 10000, Vietnam
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Research Institute for Marine Fisheries, Ministry of Agriculture and Environment, 224 Le Lai Street, Ngo Quyen, Haiphong City 04000, Vietnam
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Institute of Science and Technology for Energy and Environment, Vietnam Academy of Science and Technology (VAST), 18 Hoang Quoc Viet, Nghia Do, Hanoi 10000, Vietnam
Diversity2025, 17(12), 863;https://doi.org/10.3390/d17120863
This article belongs to the Special Issue Diversity in 2025
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Abstract

Vietnam, a coastal and tropical country, harbors a high diversity of marine mollusks, particularly gastropods and bivalves. However, the taxonomy of these groups is frequently confounded by their morphological similarities and pronounced plasticity. The aim of this study was to assemble the first comprehensive barcode reference library for marine gastropods and bivalves in Vietnam. The samples were collected from four different marine areas. We identified 31 morphospecies belonging to 28 genera, 24 families, and 11 orders. A total of 49 COI-5P sequences were obtained and categorized into 31 taxa (30 to species levels), 83.67% of which were found to be concordant with morphology-based identifications. The topology of Neighbor-Joining trees also grouped the sequences of the same species into monophyletic clusters, which were congruent with 31 taxa. Twenty eight species were placed in single Barcode Index Numbers (BINS) and three in two BINs. Barcode gaps were found for all species. As a result, the obtained COI-5P barcodes are suitable for species identification of 17 gastropod species and 14 bivalves. All COI-5P barcodes have been deposited in GenBank, BOLD, and the website for the national project “Development of DNA Database for Valuable Marine Invertebrates”.

1. Introduction

Oceans cover more than 70% of the Earth’s surface and harbor over 230,000 known species [1]. Mollusks account for 23% of marine animals, with the number of named species ranging between 34,000 [2], 52,000 [3], and 70,000 [4]. The phylum Mollusca is divided into eight taxonomical classes, with Gastropoda being the largest group, followed by Bivalvia [5]. Marine gastropods and bivalves alone comprise approximately 64,000 and 21,000 described living species, respectively, worldwide [1]. They contribute substantially to marine biodiversity and ecosystem dynamics by functioning as both predators and prey. In addition, they are widely used by humans as food sources and for pharmaceutical and nutraceutical applications [6].
Despite being important marine invertebrate groups, the taxonomy of marine gastropods and bivalves remains challenging due to their high diversity [7,8]. Specimen identification and species delimitation in these classes still largely rely on morphology, which can over- or underestimate species diversity because of shell plasticity and convergence morphology [9,10,11,12]. Accurate specimen identification is fundamental to various research fields, such as biodiversity, biogeography, and natural resource assessment and management [13,14]. Therefore, improving the precision of species determination is of primary importance.
In recent decades, molluscan molecular systematics has made significant progress through the application of DNA barcoding [15]. A specific and short DNA fragment is compared against a database of reference sequences, allowing for rapid and accurate species determination, particularly for cryptic species or closely related taxa that may be difficult to distinguish based on morphology alone. Mitochondrial DNA, especially a segment of the cytochrome c oxidase I (COI) gene, is widely used for DNA barcoding because of its high copy number, lack of introns, limited recombination, relatively high mutation rate, and maternal inheritance [16]. A range of primers, designed to bind to conserved regions of the COI gene, have been developed to amplify a standard fragment of the COI gene, especially its 5’ region, for DNA barcoding of a wide range of animal phyla [17]. To date, many DNA barcoding studies on marine mollusks [18,19,20,21,22,23] have generated a substantial corpus of COI barcodes, which are stored in GenBank and the Barcode of Life Database (BOLD) as references and for comparative analyses.
Vietnam is a coastal country with a shoreline exceeding 3260 km and more than 3000 islands, including the offshore archipelagos of Hoang Sa and Truong Sa [24]. The country is recognized as a global center of marine biodiversity, with over 11,000 recorded marine species, including a rich assemblage of marine mollusks [25].
At least 2500 mollusk species have been recorded, approximately one-fifth of all marine organisms identified along the coast of the Eastern Sea [26]. However, information on their species composition, abundance, and spatial distribution across sea regions remains incomplete. Recently, DNA barcoding has been applied to the cephalopod group, in which 41 cephalopod samples from the Gulf of Tonkin were identified as 14 species using the COI gene [22]. However, the broader applicability of barcoding remains limited for regional mollusks, particularly marine gastropods and bivalves, because of the paucity of curated DNA barcode reference sequences.
Hence, in this study, a DNA barcode reference database for the marine gastropod and bivalve taxa of Vietnam was developed. The congruence between morphology-based classification and DNA barcoding identification was assessed, and the new sequences herein were compared with records in public repositories. To validate the DNA barcodes, we used similarity blasting against existing records, created taxon neighbor-joining trees to check for monophyly, and analyzed genetic distances to confirm a clear separation between intra- and inter-specific genetic variations.

2. Materials and Methods

2.1. Sample Collection

Sampling was conducted in Ha Long and Bai Tu Long bays and Phu Quoc and Con Dao islands in Vietnam (Figure 1). Ha Long and Bai Tu Long bays are situated in northeastern Vietnam and are classic karst seascapes characterized by submerged limestone, with numberless impressive cones and tower-like islets, and extensive coastal erosion features. Phu Quoc (southwestern Vietnam) and Con Dao (southern Vietnam) are large archipelagos comprising 18 and 16 islands, respectively.
Figure 1. Sampling locations. A. Ha Long and Bai Tu Long bays. B. Phu Quoc Islands. C. Con Dao Islands. Sampling method: SCUBA diving; mollusk habitat: coral reef interspersed with rocky substrate; sample storage site: Institute of Chemistry, Vietnam Academy of Science and Technology.
A total of 49 molluscan specimens (Gastropod and Bivalve) were collected between May 2023 and May 2025: 10 samples (~20%) were collected from two localities in Bai Tu Long Bay and Ha Long Bay, 20 (~41%) from seven localities in the Con Dao Islands, and 19 (~39%) from six localities in the Phu Quoc Islands (Figure 1, Table S1). The sample size ranged from 1 to 6 individuals per morphospecies depending on field availability. The samples were transported to the laboratory on ice for genetic analyses. Each specimen was photographed, assigned a voucher ID, and deposited at the Institute of Chemistry, Vietnam Academy of Science and Technology.
Morphological identification of obtained samples was performed based on identification guides, species keys, and taxonomic descriptions [27,28,29]. It indicated that our 49 samples belong to two classes, 11 orders, 24 families, and 28 genera. Of these, 39 samples (79.59%) were morphologically identified to the species level (30 species), while 10 samples were identifiable only to the genus level. Details of the collected samples including species morphological identification are provided in Table S2 and were deposited in BOLD under Dataset DS-HMTM01.

2.2. DNA Extraction, PCR, and Sequencing

DNA was manually extracted from ~50 mg of tissue per specimen using the CTAB method [30] with some modifications. DNA yield and quality were assessed using a NanoDropTM 2000/200c spectrophotometer (Thermo Scientific, Waltham, MA, USA). The 5′ region of cytochrome c oxidase subunit I (COI-5P) was amplified by polymerase chain reaction (PCR) using the LCO1490 and HC02198 primer pair [24], as well as other primers designed for this study. The primer sequences are listed in Table S4. The reactions (50 µL) contained 25 µL of the DreamTaq PCR Master Mix (2X) (Thermo Scientific, Vilnius, Lithuania), 2 µL of 25 mM MgCl2 (Thermo Scientific, Vilnius, Lithuania), 0.5 µM of each primer, and ~10 ng of template DNA. The thermal cycling conditions were 95 °C for 3 min; 35 cycles of 95 °C for 30 s, 50–53 °C for 30 s, 72 °C for 1 min; and a final extension of 72 °C for 5 min. Amplicons were separated on 1% agarose gels stained with Redsafe (5 μL loaded per 50 mL agarose). The PCR products were purified using the GeneJET Gel Extraction Kit (Thermo Scientific, Vilnius, Lithuania) according to the manufacturer’s protocol, cloned into the pJET1.2 vector (Thermo Scientific, Vilnius, Lithuania), and bidirectionally sequenced by First Base Pte Ltd. (Singapore). Amplicons were separated on 1% agarose gels stained with Redsafe.

2.3. Sequence Analysis for Species Identification

Raw COI 5P sequences were assembled, and primer regions and ambiguous bases were trimmed using DNAMAN v10 (Lynnon Biosoft, San Ramon, CA, USA). The curated sequences were deposited in the National Center for Biotechnology Information (NCBI) (Accession Numbers: PV878089-PV878099; PV878101-PV878103; PV878105; PV882997-PV883001; PV883002-PV883003; PV883006-PV883008; PX250345; PX250348-PX250356; PX250359-PX250364; PX250367-PX250374; and PX250382) and BOLD under Project ‘HMTM-Mollusk in Vietnam_2025 analysis’. The efficiency of COI DNA barcoding for species identification was evaluated using similarity-, distance-, and tree-based approaches.
For similarity-based identification, each sequence was queried independently against GenBank and BOLD. Each sample was assigned a scientific name based on the top matches. Accepted species names were standardized according to the World Register of Marine Species (WoRMS) (www.marinespecies.org; accessed 18 August 2025). In cases where the scientific names of reference sequences from NCBI and BOLD did not match the accepted names on WoRMS, the names from NCBI and BOLD were retained for consistency with the sequence data used in this study. Based on previous studies of marine mollusks [18,20,31,32,33] a genetic similarity of 97% and genetic distance of 3% were taken as acceptable thresholds.
Barcode Index Numbers (BINs) were automatically assigned by BOLD Systems v.5 as registry identifiers, which can be used to assess the concordance between barcode sequence and nominal species. Neighbor-joining (NJ) trees, which served as a preliminary basis for species recognition, were constructed from datasets for each targeted group using the Kimura 2-parameter distance model, Taxon ID tree of BOLD Workbench (https://boldsystems.org; accessed on 28 October 2025), and MegaX [34]. The datasets for gastropods and bivalves retrieved from the study samples and species of related genera listed in BOLD and GenBank contain 413 and 118 sequences, respectively. A species was considered monophyletic when the most similar sequences formed a single, well-supported cluster [35,36], which is often congruent with a single BIN. A cluster of species with two distinct BINs can reflect deep genetic divergence within species. These trees were constructed with the aim of obtaining support values for taxa in which genetic clusters may represent existing, new or cryptic species; it was not our objective to infer phylogenetic relationships among the analyzed species.
Genetic distances, including maximum intraspecific distance within species and minimum interspecific distance, were calculated using the K2P distance model [35] and datasets including sequences of all species within targeted genus available in BOLD. Overall data were compared using the ‘Distance Summary’ and ‘Barcode Gap Analysis’ tools in BOLD (https://boldsystems.org/; accessed on 28 September 2025) [37]. The intraspecific genetic distances below the 3% threshold were considered the same species and, those higher than the 3% threshold indicate potential cryptic species, taxonomic issues, or high genetic divergence. A barcode gap exists when the maximum intraspecific distance was lower than the minimum interspecific distance.

3. Results

3.1. Similarity-Based Identifications

The COI-5P sequences of 49 samples were obtained, with lengths ranging from 440 to 719 bp. No frameshifts, mutations, or stop codons were detected in any of the amplified sequences. All of the obtained sequences meet the quality standards for DNA barcoding and were submitted to GenBank and BOLD for further analysis.
BLAST searches in GenBank and BOLD provided the same results and categorized 44/49 samples into 30 putative species, of which 27 species met the threshold value of 97–100% sequence similarity. Three samples were identified as Pinna atropurpurea G. B. Sowerby I, 1825, Morula rumphiusi Houart, 1996, and Paratapes undulatus (Born, 1778), with lower similarity values (94–100%) (Table 1). The five remaining samples (TM02DHD-79, TM122-39(L), TM115-145, TM9TT-4, and TM35-75) did not yield a species name after the BLAST search (https://blast.ncbi.nlm.nih.gov/Blast.cgi; accessed on 18 August 2025) due to the lack of available sequences in the NCBI and BOLD databases. Those five samples were labeled as Spondylus sp. and were identified to species levels as Spondylus nicobaricus Schreibers, 1793; Spondylus echinatus A. d’Orbigny 1853; and Spondylus squamosus Schreibers, 1793 by morphological analysis.
Table 1. Identification of gastropod and bivalve specimens using morphological and sequence similarity methods.
The similarity-based identification confirmed the morphological identification of 81.63% samples (40/49) at species and 85.71% samples (42/49) at genus levels. Seven of the ten samples for which we were unable to assign a species-level identification based on morphology (TM05DT-23, TM19Da-7, TM08HT-17, TM06HT-51, TM02HT-18, TM06DT-11, TM02DHD-79) were identified into four species: Conus vexillum, Isognomon isognomum, Phyllidiella zeylanica, and Spondylus squamosus (Table 1). Three other samples (TM06HT-51, TM08HT-17, TM02HT-18) were confirmed as Isognomon isognomum (similar identity > 99%). Mismatches at species or both genus and species levels were detected in seven samples (14.28%) (TM11DD-64, TM11C-249, TM7DR-30 or TM4C-131, TM9TD-216, TM10DTh-91, TM4DHD-60), five of which had more than 97% similarity with the identified species. The specimens (TM4C-131 and TM4DHD-60) originally identified as Tenguella granulata (Duclos, 1832) and Pteria peasei (Dunker, 1872) show 94% similarity with Morula rumphiusi Houart, 1996 and Pinna atropurpurea G. B. Sowerby I, 1825 sequences, respectively. However, such species assignment based on their sequences is in question, especially in the case of Pteria peasei (Dunker, 1872) and Pinna atropurpurea G. B. Sowerby I, 1825, whose external morphologies differ substantially from one another.

3.2. Tree-Based Analysis

According to sequence cluster analysis, the studied samples were classified into 31 taxa belonging to 28 genera, 24 families, 11 orders, and 2 classes (Table S3), in which 14 species belonged to 14 genera, 11 families, and 6 orders of Bivalvia, and 17 species belonged to 14 genera, 13 families, and 5 orders of Gastropoda.
The simplified summary topology patterns of the neighbor-joining tree examined with one dataset for gastropods and another for bivalves are shown in Figure 2. The full version of the trees can be seen in Figures S1 and S2. Both trees showed a total of 31 taxa (30 species and one identified to genus level), as indicated by similarity-based identification, and were separated into distinct monophyletic clusters with high bootstrap support. The clusters of 28 species were grouped from the sequences with the same BIN. Three clusters of Morula rumphiusi, Paratapes undulatus (Figure 2a), and Pinna atropurpurea (Figure 2b), which were identified to have less than 97% sequence similarity, were split into two different BINs (Figure 2) with two unique BINS for Morula rumphiusi, Paratapes undulatus.
Figure 2. Neighbor-joining trees for 31 species in this study. (a) NJ tree for 17 bivalves and (b) NJ tree for 14 gastropods. Each terminal node is labeled with the GenBank accession number preceding the species name and BIN. Right square bracket symbols indicate the clusters with 2 BINs. The studied sequences are marked in blue font.

3.3. DNA Barcode Gap Analysis

For each species and their congeneric references retrieved from BOLD in the dataset, the maximum intraspecific distance ranged from 0.16% to 5.95%, whereas the minimum interspecific distance ranged from 4.46% to 27.05% across the 31 taxa (Table 2). Based on the Barcode Gap analysis, the minimum interspecific distance for 31 species was larger than the maximum intraspecific distance. Therefore, there is no overlap between the distribution of maximum intraspecific and nearest-neighbor distances for either gastropods or bivalves. A barcode gap was present for all species in this study.
Table 2. Barcode gap and cluster-sequence analyses for 31 mollusk species based on divergence metrics from 49 COI-5’ sequences.
The levels of genetic distance in the COI genes of 31 species are summarized in Table 2. The maximum intraspecific distances lower than 3% threshold was found in 28 species and the exceeding value (5.95%, 5.29%, and 6.04%) was only observed in three species Morula rumphiusi Houart, 1996, Paratapes undulatus (Born, 1778), and Pinna atropurpurea G. B. Sowerby I, 1825. For Dendostrea frons (Linnaeus, 1758) and Halgerda batangas Carlson & Hoff, 2000, the maximum intraspecific distances were 0.7% and 1.35%, respectively, whereas their nearest-neighbor distances were only 1.6% and 2.1%, both below the 3% cut-off, indicating a weak barcode gap (Table 2).

4. Discussion

The study represents the first DNA barcode database for marine gastropods and bivalves from Vietnam. It demonstrated the ability of DNA barcoding to identify targeted species. However, it is not sufficient on its own for every case. There were 85.71% concordances and 14.28% mismatches at the species and/or genus levels to morphological identification. Such limitations have been repeatedly documented worldwide. For instance, large-scale barcoding studies of northwestern Pacific mollusks reported only 72.2% congruence between morphology-based identifications and BIN assignments [38]. Similarly, in the North Sea, Barco et al. [39] found 87.7% agreement between morphology and COI sequences, with the accuracy improving to 93.8%. The disagreement between two identification methods in seven samples (14.28%) should be highlighted for further investigation. Five of them (TM11DD-64, TM11C-249, TM9TD-216, TM10DTh-91, TM11TT-127) were identified as Cellana toreuma (Reeve, 1855), Conus caracteristicus Fischer von Waldheim, 1807, Dendostrea frons (Linnaeus, 1758), Donax cuneatus Linnaeus, 1758, and Turris undosa (Lamarck, 1816) with 97% sequence similarities to referenced species, a single BIN for each, and clear barcode gaps. Such data strongly suggests the samples are the same species, so the discrepancy likely arises from an issue with morphological analysis. Morphological misidentifications of specimens are common errors [40,41], often due to imprecise original species descriptions [42,43] or the use of synonyms and alternative names for the same taxon. For example, the oyster known by the synonym Magallana gigas is more commonly referred to as Crassostrea gigas [44,45]. The specimen (TM4DHD-60), originally identified as Pteria peasei (Dunker, 1872), was identified as Pinna atropurpurea G. B. Sowerby I, 1825. The clear difference in morphology between the two (Figure S3) raises problems during laboratory procedures. Specimen and/or tissue sample mislabeling and cross-contamination have been reported as possible errors during operation [46,47]. In the case of sample TM4C-131, which was originally identified as Tenguella granulata (Duclos, 1832), the barcode assigned it to Morula rumphiusi Houart, 1996, with a similarity below the 97% threshold. This indicates that the sample likely represents a different species, rather than a variant of the originally identified one. However, because the 97% threshold is based on historical data and may be misleading, additional evidence from other gene regions should be investigated to achieve a more definitive species identification for this sample.
Besides being a species identification method, the BIN system can identify taxonomic problems in our mollusks, such as cryptic species, by pointing out when a single species name is associated with multiple distinct BINs. These complex taxa can be observed through the occurrence of the same species names appearing in two clearly separate BINs. For example, Morula rumphiusi, Paratapes undulatus, and Pinna atropurpurea each appear in two distinct BINs. This work clearly demonstrates the added value of molecular tools in resolving cases where morphological evidence is inconclusive. For example, de Araújo et al. [21] showed that DNA barcoding can delimit molluscan species that are morphologically similar yet genetically distinct, underscoring the need to integrate molecular and morphological data. Taken together, these findings indicate that, while morphology is the essential foundation of taxonomy, its limitations reinforce the importance of molecular barcoding as a complementary and often decisive tool for species identification.
There is no single genetic distance threshold for separating all marine mollusk species, but a widely used guideline is a 2–3% divergence in the COI barcode region [15]. A threshold of 3% variation seems appropriate for species separation of our samples. While sample sequences acquired into single BINs have an intraspecific distance of less than 3%, the ones with intraspecific divergences greater than the 3% threshold, for example, Morula rumphiusi, were separated into two different BINs, predicting detectable intraspecific variation or the probable presence of more than one species within the nominal taxon. In the case of Pinna atropurpurea, the observed intraspecific divergence greater than 3% along with distinct BINs also suggests potential cryptic diversity or intraspecific structuring. This level of divergence is not uncommon in Pinna species. For instance, studies on Pinna rudis and Pinna nobilis showed significant genetic differentiation and high haplotype diversity, indicating the presence of cryptic species or population subdivision [48,49]. These findings highlight that a fixed threshold like 3% COI divergence may not be applicable to all species, especially those with complex population structures. Kartavtsev [49] also suggests that divergence thresholds should be flexible and considers genetic divergence as an indicator of distinct evolutionary lineages, even below 3%. This supports the idea that in Pinna atropurpurea, the high divergence and multiple BINs may reflect significant genetic variation, rather than multiple species. Furthermore, Kartavtsev et al. [50] noted the significant mitogenome variability in mussel species, reinforcing the idea that Bivalvia species, like Pinna, can exhibit considerable intraspecific divergence.
Barcode sequence divergences within nominal species are not a rare phenomenon in marine gastropods and bivalves. Layton et al. [51] reported maximum intraspecific K2P distances of 26.39% in Triopha catalinae (J. G. Cooper, 1863), 8.34% in Mya truncate Linnaeus, 1758; 3.54% in Cylichna cf. gouldii, and 9.65% in Cryptonatica affinis (Gmelin, 1791) from Canadian waters. Previously, several cryptic or complex species within gastropods and bivalves have been efficiently resolved using COI DNA barcoding [19,39,52,53,54]. In Dendostrea frons (Linnaeus, 1758) and Halgerda batangas Carlson & Hoff, 2000, the minimum interspecific (nearest-neighbor) distances were 1.6% and 2.1%, respectively, below the 3% cutoff, indicating a weak or absent barcode gap (Table 2). Such low interspecific separations may reflect recent divergence or incomplete lineage sorting; introgression/hybridization with the nearest congeners and between the not-nearest as well cannot be excluded. Definitive resolution of species limits in these cases will require broader sampling and multilocus data. These results indicate the need for deeper analyses, integrating diagnostic morphology and expert taxonomic reviews, to resolve misidentifications and taxonomic issues.
Insufficient reference coverage hindered barcode gap assessment for Morula rumphiusi and Paratapes undulatus. Although both were assigned novel BINs (BOLD:AGY2653 and BOLD:AGY2184), no additional conspecific COI 5’ sequences are available in BOLD for comparison, precluding a robust evaluation of the maximum intraspecific and minimum interspecific (nearest-neighbor) distances (Table 2). These records therefore constitute BIN singletons. The absence of additional sequence data for these species highlights the limitations of barcode gap analysis when taxa are underrepresented in reference databases. This issue is consistent with the findings of Sun et al. [38], who emphasized that extensive sampling is essential for reliable application of barcode gap criteria in species delimitation. Further research and database expansion are needed to ensure that species such as Morula rumphiusi and Paratapes undulatus are more fully represented in public repositories, thereby improving the robustness of barcode-based species identification.

5. Conclusions

In this study, the first barcode reference library for Vietnamese marine species was assembled, comprising 49 COI-5P barcodes for 17 gastropod and 14 bivalve species. These barcodes were validated through sequence similarity analyses (GenBank/BOLD), trees (NJ/BIN), and barcode gap diagnostics. Barcode gaps were detected for all species, with no overlap between maximum intraspecific and nearest-neighbor (interspecific) distances. No discordant BINs were generated from our sequences. All barcode sequences have been deposited in GenBank, BOLD, and the Vietnam marine species barcode reference library. The study findings will contribute to more efficient monitoring, conservation, and management of marine species regionally as well as worldwide.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/d17120863/s1. Table S1. Sampling detail of 49 marine gastropod and bivalve samples, Table S2. Identification of 49 molluscan specimens based on morphology and COI-5P BLAST against GenBank and BOLD, Table S3. Higher taxonomy (class, order, family) of the studied molluscan species, Table S4. Primer sets employed in amplification of the COI barcode region from studied samples; Figure S1. Taxon ID tree of bivalive species, Figure S2. Taxon ID tree of gastropod species, Figure S3. Morphology identification of samples TM8DD-49, TM4C-131, TM7TD-173 and TM4DHD-60.

Author Contributions

Conceptualization, T.M.L., L.Q.T. and N.T.V.; methodology, N.C.M., T.M.L., P.T.H. and L.Q.T.; validation, T.M.L., N.C.M., L.X.H., H.D.C., D.C.T., B.M.T., P.T.D.N. and L.Q.L.; investigation, N.C.M., P.T.H., L.X.H., H.D.C., D.C.T., B.M.T., L.Q.L. and P.T.D.N.; resources, L.X.H., H.D.C., D.C.T., B.M.T., P.T.H. and P.T.D.N.; data curation, T.M.L., N.C.M., N.T.V. and L.Q.T.; writing—original draft preparation, N.T.V.; writing—review and editing, L.Q.T. and T.M.L.; visualization, T.M.L.; supervision, T.M.L.; project administration, T.M.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Ministry of Science and Technology of Vietnam for the project “Development of a DNA database for Valuable Marine Invertebrates (Sponges, Echinoderms, and Mollusks) in Vietnam” (project code: ĐTĐLCN.62/22) (P.I.: Dr. Tran My Linh).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. MolluscaBase (Ed.) MolluscaBase. Available online: https://www.molluscabase.org (accessed on 25 September 2025).
  2. Boss, K.J. Critical estimate of the number of recent Mollusca. Occas. Pap. Mollusks 1971, 3, 81–135. [Google Scholar]
  3. Benkendorff, K. Molluscan biological and chemical diversity: Secondary metabolites and medicinal resources produced by marine molluscs. Biol. Rev. 2010, 85, 757–775. [Google Scholar] [CrossRef] [PubMed]
  4. Rosenberg, G. A New Critical Estimate of Named Species-Level Diversity of the Recent Mollusca. Am. Malacol. Bull. 2014, 32, 308–322. [Google Scholar] [CrossRef]
  5. Geiger, D.L. Marine Gastropoda. In The Mollusks: A Guide to Their Study, Collection, and Preservation; Sturm, C.F., Pearce, T.A., Valdés, A., Eds.; American Malacological Society: Pittsburgh, PA, USA, 2006; pp. 295–312. [Google Scholar]
  6. Mitra, B.; Ghosh, J. A Synoptic review on the traditional uses of gastropods and bivalves (Mollusca) as food and medicines in India. In The Basic Handbook of Indian Ethnobotany and Traditional Medicine; Sarkar, B.S., Biswas, J., Samalr, A.C., Pandey, A., Eds.; International Academic Publishing House (IAPH): Online, 2023; Volume 2, pp. 89–97. [Google Scholar] [CrossRef]
  7. Simone, L. New species, misidentifications and problematic taxonomy of some Atlantic South American marine mollusks: A review. Papéis Avulsos Zool. 2024, 64, e202464031. [Google Scholar] [CrossRef]
  8. Xu, B.; Kong, L.; Sun, J.; Zhang, J.; Zhang, Y.; Song, H.; Li, Q.; Uribe, J.E.; Halanych, K.M.; Cai, C.; et al. Molluscan systematics: Historical perspectives and the way ahead. Biol. Rev. 2025, 100, 672–697. [Google Scholar] [CrossRef]
  9. Monti, M.M.; Nappo, A.G.; Giorgini, M. Molecular characterization of closely related species in the parasitic genus Encarsia (Hymenoptera: Aphelinidae) based on the mitochondrial cytochrome oxidase subunit I gene. Bull. Entomol. Res. 2005, 95, 401–408. [Google Scholar] [CrossRef]
  10. Whelan, N. Phenotypic plasticity and the endless forms of freshwater gastropod shells. Freshw. Mollusk Biol. Conserv. 2021, 24, 87–103. [Google Scholar] [CrossRef]
  11. Idris, M.H.; Hamli, H.; Kamal, A.H.; Ab Lah, R.; Jaafa, N.M.S.N. Study of diversity and morphometry in edible bivalves and gastropods from a coastal wetland in Sarawak. Songklanakarin J. Sci. Technol. 2021, 43, 889–896. [Google Scholar] [CrossRef]
  12. Gefaell, J.; Galindo, J.; Rolán-Alvarez, E. Shell color polymorphism in marine gastropods. Evol. Appl. 2023, 16, 202–222. [Google Scholar] [CrossRef]
  13. Baerwald, M.R.; Goodbla, A.M.; Nagarajan, R.P.; Gootenberg, J.S.; Abudayyeh, O.O.; Zhang, F.; Schreier, A.D. Rapid and accurate species identification for ecological studies and monitoring using CRISPR-based SHERLOCK. Mol. Ecol. Resour. 2020, 20, 961–970. [Google Scholar] [CrossRef]
  14. Kürzel, K.; Kaiser, S.; Lörz, A.N.; Rossel, S.; Paulus, E.; Peters, J.; Schwentner, M.; Martinez Arbizu, P.; Coleman, C.O.; Svavarsson, J.; et al. Correct species identification and its Implications for conservation using Haploniscidae (Crustacea, Isopoda) in Icelandic waters as a proxy. Front. Mar. Sci. 2022, 8, 795196. [Google Scholar] [CrossRef]
  15. Hebert, P.D.; Cywinska, A.; Ball, S.L.; deWaard, J.R. Biological identifications through DNA barcodes. Proc. Biol. Sci. 2003, 270, 313–321. [Google Scholar] [CrossRef] [PubMed]
  16. Ladoukakis, E.D.; Zouros, E. Evolution and inheritance of animal mitochondrial DNA: Rules and exceptions. J. Biol. Res. Thessalon. 2017, 24, 2. [Google Scholar] [CrossRef]
  17. Zhang, D.X.; Hewitt, G.M. Assessment of the universality and utility of a set of conserved mitochondrial COI primers in insects. Insect Mol. Biol. 1997, 6, 143–150. [Google Scholar] [CrossRef]
  18. Liu, J.; Zhang, H. DNA barcoding for species identification in deep-sea clams (Mollusca: Bivalvia: Vesicomyidae). Mitochondrial DNA A DNA Mapp. Seq. Anal. 2018, 29, 1165–1173. [Google Scholar] [CrossRef] [PubMed]
  19. Ran, K.; Li, Q.; Qi, L.; Li, W.; Kong, L. DNA barcoding for identification of marine gastropod species from Hainan island, China. Fish. Res. 2020, 225, 105504. [Google Scholar] [CrossRef]
  20. Buršić, M.; Iveša, L.; Jaklin, A.; Arko Pijevac, M.; Kučinić, M.; Štifanić, M.; Neal, L.; Bruvo Mađarić, B. DNA barcoding of marine mollusks associated with Corallina officinalis Turfs in Southern Istria (Adriatic Sea). Diversity 2021, 13, 196. [Google Scholar] [CrossRef]
  21. de Araújo, A.D.; Carvalho, O.D.S.; Gava, S.G.; Caldeira, R.L. DNA barcoding as a valuable tool for delimiting mollusk species of the genus Biomphalaria Preston, 1910 (Gastropoda: Planorbidae). Front. Cell. Infect. Microbiol. 2023, 13, 1167787. [Google Scholar] [CrossRef]
  22. Nguyen, T.D.; Van Nguyen, Q.; Van Pham, C.; Nguyen, M.T.; Tran, L.X.; Pham, H.M.; Vu, T.Q.; Do, T.D. Application of DNA barcoding for the identification of cephalopod species in the Gulf of Tonkin, Vietnam. Mar. Biodivers. 2025, 55, 59. [Google Scholar] [CrossRef]
  23. Setiamarga, D.H.E.; Shimizu, M.; Nakashima, S.; Osaki, C.; Hirota, K.; Anggraeni, L.; Van Tu, D.; Sasaki, T. DNA barcoding of museum-vouchered samples collected from fish markets reveals an unexpected diversity of consumed gastropods in Vietnam. Future Foods 2025, 12, 100689. [Google Scholar] [CrossRef]
  24. Giang, P.Q.; Khanal, R. What next for marine ecosystem management in Vietnam: Assessment of coastal economy, climate change, and policy implication. Environ. Res. Commun. 2024, 6, 025002. [Google Scholar] [CrossRef]
  25. Do Cong, T. Research results of biological resources and biodiversity of Vietnam sea: Current status, treats, proposed solutions to use lasting. Vietnam J. Mar. Sci. Technol. 2022, 22, 1–20. [Google Scholar] [CrossRef]
  26. Hylleberg, J.; Kilburn, R. Marine molluscs of Vietnam: Annotations, voucher material, and species in need of verification. Phuket Mar. Biol. Cent. Spec. Publ. 2003, 28, 1–299. [Google Scholar]
  27. Carpenter, K.E.; Niem, V.H. FAO Species Identification Guide for Fishery Purposes. The Living Marine Resources of the Western Central Pacific. Volume 2. Seaweeds, Corals, Bivalves and Gastropods; FAO: Rome, Italy, 1998; p. 700. [Google Scholar]
  28. Okutani, T. Marine Mollusks in Japan; Tokai University Press: Tokyo, Japan, 2000; p. 1173. [Google Scholar]
  29. Jela, C.; Monteclaro, H.; Añasco, N.; Quinitio, G.; Babaran, R. Identification of pen shells (Bivalvia: Ostreida: Pinnidae) collected off northern Iloilo, Philippines using their morphological characters. Acta Ichthyol. Piscat. 2024, 54, 49–61. [Google Scholar] [CrossRef]
  30. Doyle, J.J.; Doyle, J.L. A Rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem. Bull. 1987, 19, 11–15. [Google Scholar]
  31. Meyer, C.P.; Paulay, G. DNA Barcoding: Error rates based on comprehensive sampling. PLoS Biol. 2005, 3, e422. [Google Scholar] [CrossRef]
  32. Audzijonyte, A.; Krylova, E.M.; Sahling, H.; Vrijenhoek, R.C. Molecular taxonomy reveals broad trans-oceanic distributions and high species diversity of deep-sea clams (Bivalvia: Vesicomyidae: Pliocardiinae) in chemosynthetic environments. Syst. Biodivers. 2012, 10, 403–415. [Google Scholar] [CrossRef]
  33. Breure, A.S.H. Caribbean Bulimulus revisited: Physical moves and molecular traces (Mollusca, Gastropoda, Bulimulidae). PeerJ 2016, 4, e1836. [Google Scholar] [CrossRef]
  34. 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]
  35. Kimura, M.A. Simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol. 1980, 16, 111–120. [Google Scholar] [CrossRef]
  36. Tamura, K.; Peterson, D.; Peterson, N.; Stecher, G.; Nei, M.; Kumar, S. MEGA5: Molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol. Biol. Evol. 2011, 28, 2731–2739. [Google Scholar] [CrossRef] [PubMed]
  37. Ratnasingham, S.; Hebert, P.D. BOLD: The Barcode of Life Data System. Mol. Ecol. Notes 2007, 7, 355–364. [Google Scholar] [CrossRef] [PubMed]
  38. Sun, S.E.; Li, Q.; Kong, L.; Yu, H.; Zheng, X.; Yu, R.; Dai, L.; Sun, Y.; Chen, J.; Liu, J.; et al. DNA barcoding reveal patterns of species diversity among northwestern Pacific molluscs. Sci. Rep. 2016, 6, 33367. [Google Scholar] [CrossRef] [PubMed][Green Version]
  39. Barco, A.; Raupach, M.; Laakmann, S.; Neumann, H.; Knebelsberger, T. Identification of North Sea molluscs with DNA barcoding. Mol. Ecol. Resour. 2016, 16, 288–297. [Google Scholar] [CrossRef]
  40. Lis, J.A.; Lis, B.; Ziaja, D.J. In BOLD we trust? A commentary on the reliability of specimen identification for DNA barcoding: A case study on burrower bugs (Hemiptera: Heteroptera: Cydnidae). Zootaxa 2016, 4114, 83–86. [Google Scholar] [CrossRef]
  41. Pentinsaari, M.; Ratnasingham, S.; Miller, S.E.; Hebert, P.D.N. BOLD and GenBank revisited—Do identification errors arise in the lab or in the sequence libraries? PLoS ONE 2020, 15, e0231814. [Google Scholar] [CrossRef]
  42. Thessen, A.E.; Patterson, D.J.; Murray, S.A. The Taxonomic Significance of Species That Have Only Been Observed Once: The Genus Gymnodinium (Dinoflagellata) as an Example. PLoS ONE 2012, 7, e44015. [Google Scholar] [CrossRef]
  43. Padial, J.M.; De la Riva, I. A paradigm shift in our view of species drives current trends in biological classification. Biol. Rev. 2021, 96, 731–751. [Google Scholar] [CrossRef]
  44. Bayne, B.; Ahrens, M.; Allen, S.; Anglès d’Auriac, M.; Backeljau, T.; Beninger, P.; Bohn, R.; Boudry, P.; Davis, J.; Green, T.; et al. The Proposed Dropping of the Genus Crassostrea for All Pacific Cupped Oysters and Its Replacement by a New Genus Magallana: A Dissenting View. J. Shellfish Res. 2017, 36, 545–547. [Google Scholar] [CrossRef]
  45. Backeljau, T. Crassostrea gigas or Magallana gigas: A Community-based Scientific Response. NSA Newslet. 2018, 1, 3. [Google Scholar]
  46. Radulovici, A.; Vieira, P.; Duarte, S.; Teixeira, M.; Borges, L.; Deagle, B.; Majaneva, S.; Redmond, N.; Schultz, J.; Costa, F. Revision and annotation of DNA barcode records for marine invertebrates: Report of the 8th iBOL conference hackathon. Metabarcoding Metagenomics 2021, 5, e67862. [Google Scholar] [CrossRef]
  47. Lopes, E.P.; Santos, S.; Xavier, R.; Santos, J.L.; Cabezas, M.P.; Sequeira, F.; Santos, A.M. Genetic analysis of Pinna rudis L 1758 (Mollusca, Bivalvia, Pinnidae) in the Northwest Cabo Verde Islands (Central-East Atlantic). PeerJ 2025, 13, e18328. [Google Scholar] [CrossRef]
  48. Katsares, V.; Tsiora, A.; Galinou-Mitsoudi, S.; Imsiridou, A. Genetic structure of the endangered species Pinna nobilis (Mollusca: Bivalvia) inferred from mtDNA sequences. Biologia 2008, 63, 412–417. [Google Scholar] [CrossRef]
  49. Kartavtsev, Y.P. Sequence divergence at mitochondrial genes in animals: Applicability of DNA data in genetics of speciation and molecular phylogenetics. Mar. Genom. 2011, 4, 71–81. [Google Scholar] [CrossRef] [PubMed]
  50. Kartavtsev, Y.P.; Masalkova, N.A. Structure, Evolution, and Mitochondrial Genome Analysis of Mussel Species (Bivalvia, Mytilidae). Int. J. Mol. Sci. 2024, 25, 6902. [Google Scholar] [CrossRef] [PubMed]
  51. Layton, K.K.S.; Martel, A.L.; Hebert, P.D.N. Patterns of DNA Barcode Variation in Canadian Marine Molluscs. PLoS ONE 2014, 9, e95003. [Google Scholar] [CrossRef]
  52. Pejovic, I.; Ardura, A.; Miralles, L.; Arias, A.; Borrell, Y.J.; Garcia-Vazquez, E. DNA barcoding for assessment of exotic molluscs associated with maritime ports in northern Iberia. Mar. Biol. Res. 2016, 12, 168–176. [Google Scholar] [CrossRef]
  53. Affenzeller, S.; Haar, N.; Steiner, G. Revision of the genus complex Gibbula: An integrative approach to delineating the Eastern Mediterranean genera Gibbula Risso, 1826, Steromphala Gray, 1847, and Phorcus Risso, 1826 using DNA-barcoding and geometric morphometrics (Vetigastropoda, Trochoidea). Org. Divers. Evol. 2017, 17, 789–812. [Google Scholar] [CrossRef]
  54. Barco, A.; Evans, J.; Schembri, P.J.; Taviani, M.; Oliverio, M. Testing the applicability of DNA barcoding for Mediterranean species of top-shells (Gastropoda, Trochidae, Gibbula s.l.). Mar. Biol. Res. 2013, 9, 785–793. [Google Scholar] [CrossRef]
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