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Article

DNA Barcoding Is a Useful Tool for the Identification of the Family Scaridae in Hainan

1
South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization, Ministry of Agriculture and Rural Affairs, Guangzhou 510300, China
2
College of Fisheries and Life Science, Shanghai Ocean University, Shanghai 201306, China
3
Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
4
Tropical Aquaculture Research and Development Center, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Sanya 572018, China
5
Sanya Tropical Fisheries Research Institute, Sanya 572018, China
*
Author to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2022, 10(12), 1915; https://doi.org/10.3390/jmse10121915
Submission received: 11 November 2022 / Revised: 17 November 2022 / Accepted: 18 November 2022 / Published: 6 December 2022
(This article belongs to the Special Issue New Techniques in Marine Aquaculture)

Abstract

:
Species markers can be quickly and accurately assessed using DNA barcoding. We investigated samples from the parrotfish family Scaridae using DNA barcoding in Hainan. A total of 401 DNA barcodes were analyzed, including 51 new barcodes generated from fresh material, based on a 533 bp fragment of the cytochrome c oxidase subunit I (CO I) gene. There were 350 CO I barcode clusters that matched 43 species from the Barcode of Life Data Systems (BOLD) and GenBank databases. The results showed the following average nucleotide compositions for the complete dataset: adenine (A, 22.7%), thymine (T, 29.5%), cytosine (C, 29.5%), and guanine (G, 18.2%). The mean genetic distance between confamilial species was nearly 53-fold greater than that between individuals within the species. In the neighbor-joining tree of CO I sequences, Chlorurus sordidus and C. spilurus clustered together, and all other individuals clustered by species. Our results indicated that DNA barcoding could be used as an effective molecular tool for monitoring, protecting, and managing fisheries, and for elucidating taxonomic problem areas that require further investigation.

1. Introduction

Parrotfish (family Scaridae), belonging to Actinopterygii: Perciformes, are herbivorous fish that live in tropical and subtropical coral reefs and are relatively abundant in biomass [1]. They play a crucial role in coral reef ecosystems [2,3], and as consumers of benthic algae, directly affect the structure and composition of benthic communities, and positively affect coral survival and growth [4]. Parrotfish are also involved in calcium carbonate cycling in coral reefs [5,6], and decompose coral reef skeletons into sand-sized sediments [7,8]. They maintain a coral-dominated community structure by feeding on fast-growing algae and can also influence reef development and complexity by decomposing reef carbonates [2,9]. Thus, sediments produced through parrotfish activities are an important source of island construction and maintenance in atoll coral reef environments, particularly in the setting of current rising sea levels and changes in island morphology [10]. The Healthy Reef Initiative (http://www.healthyreefs.org/cms/; accessed on 1 June 2022) uses parrotfish biomass as one of the key indicators in their coral reef health reports [11]. They have beautiful body shapes and bright colors, which greatly enhance the aesthetic quality of coral reefs and improve their economic value through ecotourism [3]. They are used as important food resources, and their biomass has recently decreased because of increased fishing [12,13].
Parrotfish, which are widely distributed in tropical, subtropical, and temperate areas [14], include approximately 100 species, divided among 10 genera [15]. There are 33 species of Scaridae in Taiwan and 31 species in mainland China [16]. The fish are known to change sex (from female to male) and color (inpectoral fin color from brown to blue) during growth [12,17]. Additionally, parrotfish have a behavioral mode called “grouping crypsis” (http://fishdb.sinica.edu.tw/; accessed on 1 June 2022). Juvenile parrotfish are discolored because of their social behavior. When they swim together, regardless of whether they are of the same species, their body color responds to the majority, becoming consistently grayish-brown, or exhibiting a longitudinal gradient in these colors. Once alone, juvenile fish instantly display beautiful and bright colors that blend into the surrounding environment, and these color changes occur very quickly. These extremely variable characteristics lead to difficulties in the morphological identification of Scaridae.
In the last decade, research on parrotfish has largely focused on their role and the mechanisms of their effects on coral reef ecosystems [9,18]. These fish can be excavators, scrapers, or grazers [19]. With increasing concern about parrotfish populations, the focus has been on coral reef health [20]. Furthermore, some researchers have explored the feeding ecology, habitat, diet, and habitat shifts of parrotfish by examining their fatty acid concentrations, composition, and levels [17]. Therefore, based on the economic, development and conservation of parrotfish, it is necessary to accumulate basic information about parrotfish and develop appropriate conservation and management measures [21]. A study using otoliths to identify parrotfish found that small otoliths were most similar to large Scarus oviceps, and least similar to large Hipposcarus longiceps [22]. However, there are several obvious shortcomings in the identification of otoliths: (i) there is no complete database of otolith morphology; (ii) because of the wide variety of parrotfish, it is difficult to find enough variability in otolith shape to identify species; and (iii) polishing otoliths is time-consuming, and the loss is large. Much experience is required to accurately identify otoliths.
In the past two decades, molecular techniques have become a popular and critical method for identifying species and resolving taxonomic ambiguities [23]. Molecular methods are useful in elucidating phylogenetic relationships and evolutionary patterns for biological ecology where classical morphological methods are not applicable [24]. DNA barcoding methods have been used to complement or refine morphological species identifications [25,26]. Studies have shown that the identification and discrimination of DNA barcoding are accurate and rapid [27,28,29]. DNA barcoding has been used to identify species using cytochrome c oxidase subunit I (CO I) sequences [30]. Therefore, they have been widely used for species identification [31,32,33,34].
In this study, more parrotfish samples were investigated to further evaluate the effectiveness of DNA barcoding for distinguishing parrotfish. The objectives of this study were to examine the reliability of CO I as a DNA barcode in parrotfish gene composition, and to determine intra- and interspecific genetic distances, codon characteristics, and molecular phylogenetic trees. The DNA barcoding data generated can be used as an effective molecular tool to achieve better monitoring and conservation outcomes for the family Scaridae.

2. Material and Methods

2.1. Sample Collection

A total of 51 parrotfish were collected from Hainan and Sansha in China (collection information available in Table 1). All samples in this experiment were obtained with the assistance of local fishermen and buyers on 5 October 2018. Back muscles were collected from each sample and preserved in 95% ethanol prior to DNA extraction. All samples were preserved at the South China Sea Fisheries Research Institute, Chinese Academy of Fisheries Sciences, China.

2.2. DNA Extraction

DNA was extracted from the muscle samples using a HiPure Mollusc DNA Kit (Axygen Biosciences, San Francisco, CA, USA) according to the manufacturer’s instructions. All DNA samples were stored at −20 °C, followed by polymerase chain reaction (PCR) amplification.

2.3. PCR and DNA Sequencing

Fragments of the mitochondrial COⅠ gene were amplified using the following universal fish barcoding primers: forward fish-F 5′-TCRACYAAYCAYAAAGAYATYGGCAC-3′ and reverse fish-R 5′-ACTTCAGGGTGACCGAAGAATCAGAA-3′. The total volume and thermal cycle sequences of the PCR were performed as described previously [35]. The amplified PCR products were checked for optimal fragment sizes on 1.5% agarose gels. The PCR products with a single bright band were sent to Beijing RuiBiotec (Beijing, China) for sequencing in both directions. All sequences were loaded onto BOLD in the project.

2.4. Analysis of the Utility of the BOLD as an Identification Tool for Parrotfish

A total of 350 sequences belonging to 43 species of parrotfish with genus and species names assigned were found in a search on BOLD. In the case of these records, the number of barcoded index numbers (BIN) associated with each species was recorded. If a species was associated with a BIN, an assessment was conducted to determine whether the BIN was associated with any other species.

2.5. Data Analysis

SSR Hunter 1.3 software was used to edit the sequences, Clustal X 1.83 was used to align all the sequences, and redundant sequences at both ends were removed. Mega 7.0 was used to analyze the nucleotide composition, number of mutation sites and codon composition of all sequences. Based on the Kimura 2-parameter (K2P) model, inter and intraspecific genetic distances were calculated, molecular phylogenetic trees were constructed using the neighbor-joining (NJ) method, and their confidence was tested by 1000 repeated samplings.

2.6. Ethics Statement

All experiments in this study were conducted in accordance with the regulations and guidelines established by the Animal Care and Use Committee of the South China Sea Fisheries Research Institute of the Chinese Academy of Fishery Sciences (No. SCSFRI96-253).

3. Results

3.1. Sequence Characteristics of CO I Gene Fragment

A total of 401 CO I sequences were obtained, representing 44 species and 10 genera. All the sequences were trimmed to a consensus length of 533 bp. The mean nucleotide compositions for the complete data set were as follows: 22.7% adenine (A), 29.5% thymine (T), 29.5% cytosine (C), and 18.2% guanine (G). The highest percentage of G-C (55.69%) was detected in the first codon, whereas the lowest (42.96%) was detected in the second codon (Table 2). Within the 533-bp nucleotide sequences in the complete data set, there were conserved sites (327, 61.53%), variable sites (204, 38.27%), parsimony-informative sites (194, 36.40%), and singleton sites (10, 1.88%). Transitional pairs (si = 458) were present in greater numbers than transversional pairs (sv = 52). The ratio of si/sv (R) was 21.00 for the data set (Table 2).

3.2. Genetic Distance between Species and within Species

Intraspecific K2P distances ranged from 0.000 to 0.015, and most intraspecific genetic distances were below 0.01. There were four species with intraspecific genetic distances between 0.01 and 0.02 (Figure 1). The mean intraspecific genetic distance was 0.003. Among the 44 species, Scarus flavipectoralis and Nicholsina usta had the greatest interspecific genetic distance of 0.248, while Chlorurus sordidus and C. spilurus had the lowest interspecific genetic distance (0.002). Most interspecific genetic distances were above 0.1. Overall, the mean interspecific genetic distance was 0.159, nearly 53 times higher than that among individuals within the same species (Supplementary Table S1).

3.3. Molecular Phylogenetic Tree

The NJ tree clustered C. sordidus and C. spilurus together, while the other individuals clustered by species (Figure 2). There were close relationships between C. japanensis and C. capistratoides, C. carolinus, and C. viridescens; S. rivulatus and S. globiceps; S. rubroviolaceus and S. ghobban and S. schlegeli and S. ferrugineus, which together formed a cohesive group with a moderately significant bootstrap value above 80%. Simultaneously, Chlorurus, Cryptotomus, Nicholsina, Leptoscarus, Hipposcarus, Bolbometopon, Sparisoma, Calotomus, Cetoscarus, and Scarus clustered into separate branches.

3.4. New Country Records

Based on the samples collected, identified, and processed in this study, and a BLAST search in the BOLD and GenBank databases, three species, C. carolinus, C. japanensis, and S. rivulatus, are reported from mainland China for the first time. This increases the parrotfish diversity for mainland China species.

4. Discussion

CO I is commonly used as a barcode marker for animal species when the intraspecific K2P distance is below 1% and rarely exceeds 2% [36]. Hebert et al. suggested that the key point for the effective identification of species using CO I gene sequences is that the interspecific genetic distance must be greater than the intraspecific genetic distance, and the distances must differ by approximately 10 times [36,37]. The mean intraspecific genetic distance was 0.003 for the entire data set. The average interspecific genetic distance of the entire data set was 53 times that of average intraspecific genetic distance. The NJ tree clustered C. sordidus and C. spilurus together, and all other individuals clustered together by species, with high confidence. These results indicate that the CO I gene sequence can be used to effectively identify species in the family Scaridae.
On average, a G-C content of 47.75% was detected in the dataset. The base composition characteristics of the CO I gene were consistent with those reported for other teleosts, all of which had a GC content lower than AT content [38,39]. The first codon had the highest G + C content (48.3%), and the variation range was 53.39–56.74%. The second codon had the lowest G + C content (42.96%), and the variation range was 41.57–44.94%. The G + C content of the 3rd codon was 44.53%, ranging from 30.86–52.57%. In the CO I gene, si is often greater than sv, and the smaller the ratio R, the faster the evolutionary rate. In this study, the first and third codons had the largest and smallest R-values, respectively; the third codon had the fastest evolutionary rate, and the first codon the slowest. The possible explanation for this result might be that the variation range of G + C content is directly related to the evolution rate of codons. The larger the variation range of G + C content, the faster the evolution rate of codons.
The greatest genetic distance within the species was less than the smallest genetic distance between species, and a barcode gap was generated. Barcode gap is a key factor for the accurate identification of species from DNA barcodes. The intraspecific genetic distances of C. sordidus and C. spirus were 0.005 and 0.000, respectively. The interspecific genetic distance between the two species was 0.003. No barcode gaps were observed between the two species. In the NJ phylogenetic tree, C. sordidus and C. spilurus formed independent branches with a confidence level of 88. Therefore, the results of this study are identical to those of earlier studies, supporting the assertion that C. spilurus and C. sordidus are the same species [16].
The divergence between Chlorurus and Scarus was quite close, 6.0–7.4 mya, and the genera Chloruus and Scarus showed most of the variation after 3–5 million years [40]. However, Bellwood regarded the genera Chlorurus and Scarus as two distinct monophyletic lineages [41]. The topological structure reinforced the morphological diagnosis that these two genera belong to a monophyletic lineage, and together form a good clade [39]. Bayesian analysis was consistent with previous studies that provided strong support for confirming the identity of Chlorurus and Scarus [42]. In our study, Chlorurus and Scarus clustered into two independent branches, verifying the morphological diagnosis. In the phylogenetic tree, fish species of each genus formed an independent branch. Therefore, CO I is also suitable for identification at the genus level in the Scaridae.
The International Barcode of Life (iBOL, http://ibol.org/; accessed on 2 June 2022) is the global leader in DNA barcode work, determining species based on DNA barcodes, and sharing results freely [43]. Notably, the development of DNA barcode libraries is based on community efforts, and the use of the BOLD has led to DNA barcode technology being regarded as the standard for species recognition [38]. In BOLD, barcode sequences are stored and associated with other taxonomic data (voucher images, location data, etc.) to improve the accuracy of species recognition [44]. The BOLD has accelerated exchanges between countries worldwide, enabling global resources to be interoperable and species identification to be more standardized. BOLD is an accessible database for the analysis and search of DNA barcode data [45]. International life barcodes have several shortcomings: (i) Data sharing is not timely. Data provided by countries to the BLOD can be made public after only two years, because researchers hope to disclose the data only after analysis or article publication. (ii) According to the BLOD standards for data management, each DNA barcode must have complete voucher specimen information, acquisition information, and the original files of the sequenced peak map. However, many research groups and researchers from China cannot strictly follow these requirements and standards, and the quality of the data is greatly reduced. (iii) The data were not updated in time to match the genetic sequences of the same species, which were still identified by a previous name. Therefore, the entries were not unified. Although C. sordidus and C. spilurus belong to the same genus, their genetic distance is very small, and C. spilurensis syn. nov. is therefore synonymized with C. sordidus [16], and they cluster together in a molecular evolutionary tree. However, when the sequences are aligned in BOLD, they do not have the same species names.

5. Conclusions

By analyzing the sequences of the CO I gene of 401 parrotfish, we found that the average intraspecific genetic distance was 0.003, and the average interspecific genetic distance was 0.159, approximately 53 times the average intraspecific genetic distance. The NJ tree shows that C. sordidus and C. spilurus of blue-headed green parrotfish gather together, and individuals of other species grouped together, with high support, and different species can be effectively distinguished. The results showed that DNA barcode technology based on the CO I gene could be used to identify species of Scaridae.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/jmse10121915/s1, Table S1: Mean percent genetic distances between Scaridae species under the corrected K2P.

Author Contributions

Data curation, B.L. (Bo Liu).; formal analysis, N.Z.; investigation, H.G.; methodology, J.Y.; resources, Y.Y., N.Z., H.G., B.L. (Baosuo Liu) and K.Z.; validation, B.L. (Baosuo Liu); visualization, J.Y.; writing—original draft, B.L. (Bo Liu); writing—review & editing, D.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Financial Fund of Ministry of Agriculture and Rural affairs of China (NHYYSWZZZYKZX2020), National Marine Genetic Resource Center, and China-ASEAN Maritime Cooperation Fund.

Institutional Review Board Statement

All experiments in this study were approved by the Animal Care and Use Committee of South China Sea fisheries Research Institute, Chinese Academy of fishery Sciences (no. SCSFRI96-253) and performed according to the regulations and guidelines established by this committee. Written informed consent was obtained from the owners for the participation of their animals in this study.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study. Written informed con-sent has been obtained from the patients to publish this paper.

Data Availability Statement

All data generated or analyzed during this study are included in this published article.

Acknowledgments

This work was supported by the Financial Fund of Ministry of Agriculture and Rural affairs of China (NHYYSWZZZYKZX2020), National Marine Genetic Resource Center, and China-ASEAN Maritime Cooperation Fund.

Conflicts of Interest

No potential conflict of interest was reported by the authors.

References

  1. Francini-Filho, R.B.; Moura, R.L. Evidence for spillover of reef fishes from a no-take marine reserve: An evaluation using the before-after control-impact (BACI) approach. Fish. Res. 2008, 93, 346–356. [Google Scholar] [CrossRef]
  2. Bellwood, D.R.; Hoey, A.S.; Choat, J.H. Limited functional redundancy in high diversity systems: Resilience and ecosystem function on coral reefs. Ecol. Lett. 2003, 6, 281–285. [Google Scholar] [CrossRef]
  3. Carlon, D.B.; LippÉ, C. Isolation and characterization of 17 new microsatellite markers for the ember parrotfish Scarus rubroviolaceus, and cross-amplification in four other parrotfish species. Mol. Ecol. Notes 2007, 7, 613–616. [Google Scholar] [CrossRef]
  4. Mumby, P.J.; Dahlgren, C.P.; Harbome, A.R.; Kappel, C.V.; Micheli, F.; Brumbaugh, D.R.; Holmes, K.E.; Mendes, J.M.; Broad, K.; Sanchirico, J.N.; et al. Fishing, Trophic Cascades, and the Process of Grazing on Coral Reefs. Science 2006, 311, 98. [Google Scholar] [CrossRef] [Green Version]
  5. Goatley, C.; Bellwood, D. Biologically mediated sediment fluxes on coral reefs: Sediment removal and off-reef transportation by the surgeonfish Ctenochaetus striatus. Mar. Ecol. Prog. Ser. 2010, 415, 237–245. [Google Scholar] [CrossRef] [Green Version]
  6. Glynn, P.; Manzello, D. Bioerosion and coral reef growth: A dynamic balance. In Coral Reefs in the Anthropocene; Springer: Dordrecht, The Netherlands, 2015; pp. 67–97. [Google Scholar] [CrossRef]
  7. Bellwood, D.R. Production and reworking of sediment by Parrotfish (family Scaridae) on the Great Barrier Reef, Australia. Mar. Biol. 1996, 125, 795–800. [Google Scholar] [CrossRef]
  8. Perry, C.T.; Kench, P.S.; O’Leary, M.J.; Morgan, K.; Januchowski-Hartley, F.A. Linking reef ecology to island building: Parrotfish identified as major producers of island-building sediment in the Maldives. Geology 2015, 43, 503–506. [Google Scholar] [CrossRef] [Green Version]
  9. Bellwood, D.R.; Hughes, T.P.; Folke, C.; Nystrom, M. Confronting the coral reef crisis. Nature 2004, 429, 827–833. [Google Scholar] [CrossRef] [PubMed]
  10. Morgan, K.M.; Kench, P.S. Parrotfish erosion underpins reef growth, sand talus development and island building in the Maldives. Sediment. Geol. 2016, 341, 50–57. [Google Scholar] [CrossRef]
  11. Vallès, H.; Oxenford, H.A. Simple family-level parrotfish indicators are robust to survey method. Ecol. Indic. 2018, 85, 244–252. [Google Scholar] [CrossRef]
  12. Ebisawa, A.; Ohta, I.; Uehara, M.; Nakamura, H.; Kanashiro, K.; Yasui, R. Life history variables, annual change in sex ratios with age, and total mortality observed on commercial catch on Pacific steephead parrotfish, Chlorurus microrhinos in waters off the Okinawa Island, southwestern Japan. Reg. Stud. Mar. Sci. 2016, 8, 65–76. [Google Scholar] [CrossRef]
  13. Edwards, C.B.; Friedlander, A.M.; Green, A.G.; Hardt, M.J.; Sala, E.; Sweatman, H.P.; Williams, I.D.; Zgliczynski, B.; Sandin, S.A.; Smith, J.E. Global assessment of the status of coral reef herbivorous fishes: Evidence for fishing effects. Proc. Biol. Sci. 2014, 281, 20131835. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Carpenter, K.E.; Niem, V.H. (Eds.) FAO Species Identification Guide for Fishery Purposes. Bony Fishes Part 4 (Labridae to Latimeriidae), Estuarine Crocodiles, Sea Turtles, Sea Snakes and Marine Mammals. In The Living Marine Resources of the Western Central Pacific; FAO: Rome, Italy, 2001; Volume 6, pp. 468–3492. Available online: https://ci.nii.ac.jp/ncid/BA67023968 (accessed on 1 June 2022).
  15. Nelson, J.S.; Grande, T.; Wilson, M.V.H. Fishes of the World; John Wiley & Sons: Hoboken, NJ, USA, 2016; Volume 15, pp. 429–430. [Google Scholar] [CrossRef]
  16. Wu, H.L.; Shao, G.Z.; Lai, C.F.; Chong, D.H.; Lin, P.L. Latin-Chinese Dictionary of Fish Names by Classification System; China Ocean University Press: Qingdao, China, 2017; pp. 319–320. Available online: http://cpfd.cnki.com.cn/Article/CPFDTOTAL-ZGHI201209001002.htm (accessed on 2 June 2022).
  17. Arai, T.; Amalina, R.; Bachok, Z. Similarity in the feeding ecology of parrotfish (Scaridae) in coral reef habitats of the Malaysian South China Sea, as revealed by fatty acid signatures. Biochem. Syst. Ecol. 2015, 59, 85–90. [Google Scholar] [CrossRef]
  18. Rotjan, R.D.; Dimond, J.L. Discriminating causes from consequences of persistent parrotfish corallivory. J. Exp. Mar. Biol. Ecol. 2010, 390, 188–195. [Google Scholar] [CrossRef]
  19. Francini-Filho, R.; Moura, R.; Ferreira, C.M.; Coni, E.O.C. Live coral predation by Parrotfish (Perciformes: Scaridae) in the Abrolhos Bank, eastern Brazil, with comments on the classification of species into functional groups. Neotrop. Ichthyol. 2008, 6, 191–200. [Google Scholar] [CrossRef] [Green Version]
  20. Adam, T.C.; Deron, E.B.; Ruttenberg, B.I.; Paddack, M.J. Herbivory and the Resilience of Caribbean Coral Reefs: Knowledge Gaps and Implications for Management. Mar. Ecol. Prog. Ser. 2021, 520, 1–20. [Google Scholar] [CrossRef] [Green Version]
  21. Roos, N.C.; Carvalho, A.R.; Lopes, P.F.M.; Pennino, M.G. Modeling sensitive parrotfish (Labridae: Scarini) habitats along the Brazilian coast. Mar. Environ. Res. 2015, 110, 92–100. [Google Scholar] [CrossRef]
  22. Jawad, L.A. A comparative morphological investigation of otoliths of six parrotfish species (Scaridae) from the Solomon Islands. J. Fish Biol. 2018, 93, 1046–1058. [Google Scholar] [CrossRef]
  23. Barman, A.S.; Singh, M.; Pandey, P.K. DNA barcoding and genetic diversity analyses of fishes of Kaladan River of Indo-Myanmar biodiversity hotspot. Mitochondrial DNA A 2018, 29, 367–378. [Google Scholar] [CrossRef]
  24. Ritchie, P.; Bargelloni, L.; Meyer, A.; Taylor, J.A.; Macdonald, J.A.; Lambert, D.M. Mitochondrial Phylogeny of Trematomid Fishes (Nototheniidae, Perciformes) and the Evolution of Antarctic Fish. Mol. Phylogenet. Evol. 1996, 5, 383–390. [Google Scholar] [CrossRef] [Green Version]
  25. Kochzius, M.; Seidel, C.; Antoniou, A.; Botla, S.K.; Campo, D.; Cariani, A.; Vazquez, E.G.; Hauschild, J.; Hervet, C.; Hjorleifsdottir, S.; et al. Identifying Fishes through DNA Barcodes and Microarrays. PLoS ONE 2010, 5, e12620. [Google Scholar] [CrossRef] [Green Version]
  26. Chen, W.T.; Ma, X.H.; Shen, Y.J.; Mao, Y.T.; He, S.P. The fish diversity in the upper reaches of the Salween River, Nujiang River, revealed by DNA barcoding. Sci. Rep. 2015, 5, 17437. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Ma, H.Y.; Ma, C.Y.; Ma, L.B. Molecular identification of genus Scylla (Decapoda: Portunidae) based on DNA barcoding and polymerase chain reaction. Biochem. Syst. Ecol. 2012, 41, 41–47. [Google Scholar] [CrossRef]
  28. Khedkar, G.D.; Jamdade, R.; Naik, S.; David, L.; Haymer, D. DNA barcodes for the fishes of the Narmada, one of India’s longest rivers. PLoS ONE 2014, 9, e105490. [Google Scholar] [CrossRef] [Green Version]
  29. Dhar, B.; Ghosh, S.K. Genetic assessment of ornamental fish species from North East India. Gene 2015, 555, 382–392. [Google Scholar] [CrossRef]
  30. Hebert, P.D.N.; Cywinska, A.; Ball, S.L.; de Waard, J.R. Biological identification through DNA barcodes. Proc. R. Soc. Lond. 2003, 270, 313–321. [Google Scholar] [CrossRef] [Green Version]
  31. Stein, E.D.; Martinez, M.C.; Stiles, S.; Miller, P.E.; Zakharov, E.V. Is DNA Barcoding Actually Cheaper and Faster than Traditional Morphological Methods: Results from a Survey of Freshwater Bioassessment Efforts in the United States. PLoS ONE 2014, 9, e95525. [Google Scholar] [CrossRef] [PubMed]
  32. Sethusa, M.T.; Yessoufou, K.; der Bank, M.V.; der Bank, H.V.; Sethusa, M.T.; Millar, I.M.; Jacobs, A. DNA barcode efficacy for the identification of economically important scale insects (Hemiptera: Coccoidea) in South Africa. Afr. Entomol. 2014, 22, 257–266. [Google Scholar] [CrossRef]
  33. Decru, E.; Moelants, T.; De Gelas, K.; Vreven, E.; Verheyen, E.; Snoeks, J. Taxonomic challenges in freshwater fishes: A mismatch between morphology and DNA barcoding in fish of the north-eastern part of the Congo basin. Mol. Ecol. Resour. 2016, 16, 342–352. [Google Scholar] [CrossRef] [PubMed]
  34. Nigro, L.M.; Angel, M.V.; Blachowiak-Samolyk, K.; Hopcroft, R.R.; Bucklin, A. Identification, Discrimination, and Discovery of Species of Marine Planktonic Ostracods Using DNA Barcodes. PLoS ONE 2016, 11, e0146327. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Liu, B.; Yang, J.W.; Liu, B.S.; Zhang, N.; Guo, L.; Guo, H.Y.; Zhang, D.C. Detection and identification of marine fish mislabeling in Guangzhou’s supermarkets and sushi restaurants using DNA barcoding. J. Food Sci. 2022, 87, 2440–2449. [Google Scholar] [CrossRef]
  36. Hebert, P.D.N.; Ratnasingham, S.; de Waard, J.R. Barcoding animal life: Cytochrome c oxidase subunit 1 divergences among closely related species. Proc. Biol. Sci. 2003, 270, 96–99. [Google Scholar] [CrossRef] [Green Version]
  37. Zhang, Y.H.; Qin, G.; Zhang, H.X.; Wang, X.; Lin, Q. DNA barcoding reflects the diversity and variety of brooding traits of fish species in the family Syngnathidae along China’s coast. Fish. Res. 2017, 185, 137–144. [Google Scholar] [CrossRef]
  38. Chambers, E.A.; Hebert, P.D. Assessing DNA Barcodes for Species Identification in North American Reptiles and Amphibians in Natural History Collections. PLoS ONE 2016, 11, e0154363. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  39. Sun, L.Y.; Yang, T.Y.; Meng, W.; Yang, B.Q.; Zhang, T. Analysis of the mitochondrial genome characteristics and phylogenetic relationships of eight sciaenid fishes. Mar. Sci. 2017, 41, 48–54. Available online: https://oversea.cnki.net/HYKX201703007 (accessed on 2 June 2022).
  40. Smith, L.L.; Fessler, J.L.; Alfaro, M.E.; Streelman, J.T.; Westneat, M.W. Phylogenetic relationships and the evolution of regulatory gene sequences in the Parrotfish. Mol. Phylogenet. Evol. 2008, 49, 136–152. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  41. Bellwood, D.R. A phylogenetic study of the parrotfish family Scaridae (Pisces: Labroidea), with a revision of genera. Rec. Aust. Mus. 1994, 20, 1–86. [Google Scholar] [CrossRef]
  42. Choat, J.H.; Klanten, O.S.; Herwerden, L.V.; Robertson, D.R.; Clements, K.D. Patterns and processes in the evolutionary history of Parrotfish (Family Labridae). Biol. J. Linn. Soc. 2012, 107, 529–557. [Google Scholar] [CrossRef] [Green Version]
  43. Ma, K.P. DNA barcode: From species to biome. Biodivers. Sci. 2015, 23, 279–280. [Google Scholar] [CrossRef]
  44. Barco, A.; Raupach, M.J.; Laakmann, S.; Neumnn, H.; Knebelsberger, T. Identification of North Sea molluscs with DNA barcoding. Mol. Ecol. Resour. 2016, 16, 288–297. [Google Scholar] [CrossRef]
  45. Zhang, J.B.; Hanner, R. DNA barcoding is a useful tool for the identification of marine fishes from Japan. Biochem. Syst. Ecol. 2011, 39, 31–42. [Google Scholar] [CrossRef]
Figure 1. The intraspecific genetic distances of the family Scaridae. Note: The abscissa represents the species: 1. Bolbometopon muricatum, 2. Cetoscarus ocellatus, 3. Hipposcarus longiceps, 4. Scarus iseri, 5. S. rubroviolaceus, 6. S. ghobban, 7. S. taeniopterus, 8. S. niger, 9. S. forsteni, 10. S. prasiognathos, 11. S. frenatus, 12. S. dimidiatus, 13. S. oviceps, 14. S. chameleon, 15. S. rivulatus, 16. S. globiceps, 17. S. quoyi, 18. S. flavipectoralis, 19. S. schlegeli, 20. S. fuscopurpureus, 21. S. psittacus, 22. S. pinus, 23. Chlorurus capistratoides, 24. C. japanensis, 25. C. bleekeri, 26. C. microrhinos, 27. C. frontalis, 28. C. spilurus, 29. C. sordidus, 30. Sparisoma radians, 31. S. aurofrenatum, 32. S. viride, 33. S. chrysopterum, 34. S. rubripinne, 35. S. rocha, 36. S. cretense, 37. S. atomarium, 38. Cryptotomus roseus, 39. Nicholsina denticulata, 40. N. usta, 41. Leptoscarus vaigiensis, 42. Calotlmus carolinus, 43. C. viridescens, 44. C. spinidens.
Figure 1. The intraspecific genetic distances of the family Scaridae. Note: The abscissa represents the species: 1. Bolbometopon muricatum, 2. Cetoscarus ocellatus, 3. Hipposcarus longiceps, 4. Scarus iseri, 5. S. rubroviolaceus, 6. S. ghobban, 7. S. taeniopterus, 8. S. niger, 9. S. forsteni, 10. S. prasiognathos, 11. S. frenatus, 12. S. dimidiatus, 13. S. oviceps, 14. S. chameleon, 15. S. rivulatus, 16. S. globiceps, 17. S. quoyi, 18. S. flavipectoralis, 19. S. schlegeli, 20. S. fuscopurpureus, 21. S. psittacus, 22. S. pinus, 23. Chlorurus capistratoides, 24. C. japanensis, 25. C. bleekeri, 26. C. microrhinos, 27. C. frontalis, 28. C. spilurus, 29. C. sordidus, 30. Sparisoma radians, 31. S. aurofrenatum, 32. S. viride, 33. S. chrysopterum, 34. S. rubripinne, 35. S. rocha, 36. S. cretense, 37. S. atomarium, 38. Cryptotomus roseus, 39. Nicholsina denticulata, 40. N. usta, 41. Leptoscarus vaigiensis, 42. Calotlmus carolinus, 43. C. viridescens, 44. C. spinidens.
Jmse 10 01915 g001
Figure 2. NJ tree resulting from analysis of the CO I gene for Scaridae species Bootstrap vaues Higher than 50% based on 1000 replicates are shown on the branches. The scale represents a genetic distance of 0.01 per million years.
Figure 2. NJ tree resulting from analysis of the CO I gene for Scaridae species Bootstrap vaues Higher than 50% based on 1000 replicates are shown on the branches. The scale represents a genetic distance of 0.01 per million years.
Jmse 10 01915 g002
Table 1. Voucher and sequence information for the 51 specimens. Process IDs are sequence numbers of voucher specimens in GenBank, and Voucher IDs are voucher numbers in the South China Sea Fisheries Research Institute. BOLD is a summary of identification based on the barcode sequence of each species obtained using the BOLD.
Table 1. Voucher and sequence information for the 51 specimens. Process IDs are sequence numbers of voucher specimens in GenBank, and Voucher IDs are voucher numbers in the South China Sea Fisheries Research Institute. BOLD is a summary of identification based on the barcode sequence of each species obtained using the BOLD.
GenusSpecies StudiedBOLDVoucher IDProcess IDLocation
CalotomusCalotomus carolinusCalotomus carolinusss-18MK765061Sansha
ChlorurusChlorurus japanensisChlorurus japanensisss-67MK765062Sansha
Chlorurus microrhinosChlorurus microrhinosss-53MK765063Sansha
Chlorurus microrhinosChlorurus microrhinosss-54MK765064Sansha
Chlorurus sordidusChlorurus sordidusSsfri-F0165-01MK765065Hainan
Chlorurus sordidusChlorurus sordidusSsfri-F0165-02MK765066Hainan
Chlorurus sordidusChlorurus sordidusSsfri-F0165-03MK765067Hainan
Chlorurus sordidusChlorurus sordidusSsfri-F0165-04MK765068Hainan
Chlorurus sordidusChlorurus spilurusss-16MK765069Sansha
Chlorurus sordidusChlorurus spilurusss-44MK765070Sansha
Chlorurus sordidusChlorurus spilurusss-45MK765071Sansha
HipposcarusHipposcarus longicepsHipposcarus longicepsss-17MK765072Sansha
ScarusScarus dimidiatusScarus dimidiatusss-65MK765073Sansha
Scarus chameleonScarus chameleonSsfri-F0158-02MK765074Hainan
Scarus forsteniScarus forsteniss-48MK765075Sansha
Scarus forsteniScarus forsteniss-57MK765076Sansha
Scarus forsteniScarus forsteniss-66MK765077Sansha
Scarus forsteniScarus forsteniSsfri-F0164-01MK765078Hainan
Scarus forsteniScarus forsteniSsfri-F0164-02MK765079Hainan
Scarus forsteniScarus forsteniSsfri-F0164-03MK765080Hainan
Scarus forsteniScarus forsteniSsfri-F0164-04MK765081Hainan
Scarus forsteniScarus forsteniSsfri-F0164-05MK765082Hainan
Scarus forsteniScarus forsteniSsfri-F0164-06MK765083Hainan
Scarus ghobbanScarus ghobbanss-14MK765084Sansha
Scarus ghobbanScarus ghobbanss-15MK765085Sansha
Scarus ghobbanScarus ghobbanSsfri-F0347-01MK765086Hainan
Scarus ghobbanScarus ghobbanSsfri-F0347-02MK765087Hainan
Scarus ghobbanScarus ghobbanSsfri-F0347-03MK765088Hainan
Scarus ghobbanScarus ghobbanSsfri-F0347-04MK765089Hainan
Scarus ghobbanScarus ghobbanSsfri-F0347-05MK765090Hainan
Scarus nigerScarus nigerss-7MK765091Sansha
Scarus nigerScarus nigerss-41MK765092Sansha
Scarus nigerScarus nigerss-42MK765093Sansha
Scarus ovicepsScarus ovicepsss-33MK765094Sansha
Scarus ovicepsScarus ovicepsss-46MK765095Sansha
Scarus psittacusScarus psittacusSsfri-F0171-01MK765096Hainan
Scarus psittacusScarus psittacusSsfri-F0171-02MK765097Hainan
Scarus globicepsScarus rivulatusss-93MK765098Sansha
Scarus globicepsScarus rivulatusSsfri-F0161-03MK765099Hainan
Scarus globicepsScarus rivulatusSsfri-F0161-04MK7650100Hainan
Scarus globicepsScarus rivulatusSsfri-F0161-05MK7650101Hainan
Scarus rivulatusScarus rivulatusSsfri-F0161-06MK7650102Hainan
Scarus rivulatusScarus rivulatusSsfri-F0161-07MK7650103Hainan
Scarus rivulatusScarus rivulatusSsfri-F0161-08MK7650104Hainan
Scarus rivulatusScarus rivulatusSsfri-F0161-09MK7650105Hainan
Scarus rivulatusScarus rivulatusSsfri-F0161-10MK7650106Hainan
Scarus schlegeliScarus schlegeliss-20MK7650107Sansha
Scarus schlegeliScarus schlegeliss-47MK7650108Sansha
Scarus schlegeliScarus schlegeliss-51MK7650109Sansha
Scarus schlegeliScarus schlegeliss-72MK7650110Sansha
Scarus spinusScarus spinusSsfri-F0166-01MK7650111Hainan
Table 2. Sequence variation of the CO I gene and average nucleotide frequencies of CO I partial sequences of Scaridae (%).
Table 2. Sequence variation of the CO I gene and average nucleotide frequencies of CO I partial sequences of Scaridae (%).
DomainiisisvRTCAGTotal
1 458.0052.0021.0029.529.522.718.2530.9
1st174.004.000.009.4019.027.525.328.2178.0
2nd175.002.000.005.8942.128.815.014.1178.0
3rd109.0046.0020.002.2327.532.227.912.3175.0
Note: ii = Invariant pairs; si = Transitional pairs; sv = Transversional pairs; R = si/sv.
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Liu, B.; Yan, Y.; Zhang, N.; Guo, H.; Liu, B.; Yang, J.; Zhu, K.; Zhang, D. DNA Barcoding Is a Useful Tool for the Identification of the Family Scaridae in Hainan. J. Mar. Sci. Eng. 2022, 10, 1915. https://doi.org/10.3390/jmse10121915

AMA Style

Liu B, Yan Y, Zhang N, Guo H, Liu B, Yang J, Zhu K, Zhang D. DNA Barcoding Is a Useful Tool for the Identification of the Family Scaridae in Hainan. Journal of Marine Science and Engineering. 2022; 10(12):1915. https://doi.org/10.3390/jmse10121915

Chicago/Turabian Style

Liu, Bo, Yali Yan, Nan Zhang, Huayang Guo, Baosuo Liu, Jingwen Yang, Kecheng Zhu, and Dianchang Zhang. 2022. "DNA Barcoding Is a Useful Tool for the Identification of the Family Scaridae in Hainan" Journal of Marine Science and Engineering 10, no. 12: 1915. https://doi.org/10.3390/jmse10121915

APA Style

Liu, B., Yan, Y., Zhang, N., Guo, H., Liu, B., Yang, J., Zhu, K., & Zhang, D. (2022). DNA Barcoding Is a Useful Tool for the Identification of the Family Scaridae in Hainan. Journal of Marine Science and Engineering, 10(12), 1915. https://doi.org/10.3390/jmse10121915

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