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Animal Genetics • Genet. Mol. Biol. 45 (3) • 2022 • https://doi.org/10.1590/1678-4685-GMB-2021-0349 linkcopy

Open-access Saint Peter and Saint Paul Archipelago barcoded: Fish diversity in the remoteness and DNA barcodes reference library for metabarcoding monitoring

AuthorshipSCIMAGO INSTITUTIONS RANKINGS

Abstract

In order to monitor the effects of anthropogenic pressures in ecosystems, molecular techniques can be used to characterize species composition. Among molecular markers capable of identifying species, the cytochrome c oxidase I (COI) is the most used. However, new possibilities of biodiversity profiling have become possible, in which molecular fragments of medium and short-length can now be analyzed in metabarcoding studies. Here, a survey of fishes from the Saint Peter and Saint Paul Archipelago was barcoded using the COI marker, which allowed the identification of 21 species. This paved the way to further investigate the fish biodiversity of the archipelago, transitioning from barcoding to metabarcoding analysis. As preparatory steps for future metabarcoding studies, the first extensive COI library of fishes listed for these islands was constructed and includes new data generated in this survey as well as previously available data, resulting in a final database with 9,183 sequences from 169 species and 63 families of fish. A new primer specifically designed for those fishes was tested in silico to amplify a region of 262 bp. The new approach should guarantee a reliable surveillance of the archipelago and can be used to generate policies that will enhance the archipelago’s protection.

Keywords:
Biodiversity; conservation; DNA barcoding; island; primer

Introduction

Impacts of human-induced climate change, habitat fragmentation, and over-exploitation of natural resources have depleted global biodiversity, in particular in the marine environment (Díaz et al., 2006; Butchart et al., 2010; Pinsky et al., 2019). Conservation efforts based on robust biomonitoring programs are necessary to identify and mitigate ecological issues (Stat et al., 2017; Berry et al., 2019); therefore, preservation of diversity depends on species classification accuracy (Thomsen and Willerslev, 2015; Lin et al., 2020). The species composition and distribution can act as an environmental indicator of human activity (DiBattista et al., 2020).

Species are rapidly going extinct as a result of these anthropogenic activities, and it is impossible to describe the true magnitude of the loss with traditional monitoring approaches (Blaxter, 2003; Hubert and Hanner, 2015; Zamani et al., 2022); hence, molecular techniques have been developed to characterize species diversity quickly and reliably (Krishnamurthy and Francis, 2012; Elbrecht et al., 2019). Since the early 1990s, the mitochondrial gene cytochrome c oxidase I (COI) has been used as a tool to describe biodiversity (Folmer et al., 1994). The field was revolutionized when Hebert et al. (2003) proposed that the “Folmer region” of COI could be used to identify and discriminate species as a molecular barcode (Hebert et al., 2003; Hebert and Gregory, 2005). This 658 bp genetic fragment can be easily obtained from animal tissues, and once sequenced, it provides greater than 97% confidence for differentiating species by the divergence in their COI sequences (Hajibabaei et al., 2005; Meusnier et al., 2008). After nearly two decades, the method has been widely accepted as the standard procedure for surveying biodiversity (Hubert and Hanner, 2015; Delrieu-Trottin et al., 2019).

However, for reliable species descriptions, DNA barcoding is not sufficient, and additional taxonomic approaches are necessary (Zamani et al., 2022). In fact, one of the major limitations of the technique is the need to have a reference library of DNA sequences that is built from morphologically identified species (Christoffer and Endre, 2005). This need for reference specimens imposes further difficulties because some species are rare or difficult to sample (Ogwang et al., 2020). This is exacerbated when sampling specimens from remote marine protected areas, which is the case of the Saint Peter and Saint Paul fishes.

The Saint Peter and Saint Paul Archipelago (SPSPA) is a small group of plutonic rocks uplifted from the upper mantle of the earth, located in the central equatorial Atlantic Ocean between Brazil and the African continent (Figure 1; Campos et al., 2005). The archipelago is a rare non-volcanic formation resulting from the Mid-Atlantic Ridge’s exhumed mantle rocks (Mohriak, 2020). As a consequence of unique geological traits, along with latitude, weather, marine currents, and biogeographic features, the biodiversity of the SPSPA is commensurately singular. The archipelago is an important migratory, breeding, and feeding site for fishes (Mendonça et al., 2018). Also, its isolation spawned the evolution of a unique biodiversity of fishes, with a variety of color morphs and genetically divergent lineages (Pinheiro et al., 2020).

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Figure 1 -
Saint Peter and Saint Paul Archipelago (SPSPA) in a map showing its geographical location (white square) in the Mid-Atlantic Ridge.

Due to this, the fish biodiversity of SPSPA has been intensively studied since the time when Lubbock and Edwards (1981) listed 50 fish species. The authors surprisingly considered the species diversity the lowest of any tropical island studied to date. Following the inauguration of the archipelago’s first scientific station in 1998, SCUBA (Self-Contained Underwater Breathing Apparatus) expeditions were made possible (Viana et al., 2009), and gradually the number of identified species increased from 75 (Feitoza et al., 2003) to 116 (Vaske Jr et al., 2005); and, most recently, to 225 species (Pinheiro et al., 2020). Contrary to Lubbock and Edwards’s (1981) considerations, the last survey pointed to the archipelago as having the third-highest level of endemism in the Atlantic (10 endemic species; Pinheiro et al., 2020).

Among the 225 listed species, 112 are pelagic, 86 are shallow, and 27 are deep reef shore fishes. The inventory classification consists of 202 Teleostei distributed in 16 orders and 23 Elasmobranchii in six orders (Pinheiro et al., 2020). There are at least 29 endangered species inhabiting the SPSPA waters according to the IUCN and Brazilian Red lists (Pinheiro et al., 2020). Naturally, the research collection of these species is limited by strict policies meant to protect the species; therefore, other sampling strategies are required to survey the genetic diversity of these fishes.

Fortunately, advanced molecular technologies including new DNA extraction protocols (Taberlet et al., 2018) and high-throughput sequencing have made it possible to sequence DNA molecules expelled by organisms into the environment through urine, reproductive and digestive materials, hair, skin, tissues, and decaying carcasses (Thomsen and Willerslev, 2015; Wangensteen et al., 2018). The genetic assessment of multiple taxa from bulk environmental samples is denominated “DNA metabarcoding” (Taberlet et al., 2018). And now ecologists have the necessary tools to analyze the species composition of environmental samples (Taberlet et al., 2012; Creer et al., 2016).

However, the genetic material extracted from ecosystems is highly fragmented (Deagle et al., 2006); to this extent, it may be challenging in practice to retrieve full-length COI barcode sequences (658 bp) from environmental samples (Meusnier et al., 2008). Metabarcoding analyses are contingent on targeting shorter DNA regions (<350 bp) than the traditionally defined barcoding regions (Yu et al., 2012; Clarke et al., 2014; Thomsen and Willerslev, 2015). In this context, alternative target metabarcoding markers (metabarcodes) have been developed to obtain biodiversity information in short-length (150-250 bp) PCR products (Taberlet et al., 2018).

One metabarcode option is the much shorter “mini-COI” barcode, a 130 bp fragment of the full ca. 658 bp COI barcode; Meusnier et al (2008) developed a universal primer set for the amplification of mini-COI that provides sufficient taxonomic resolution to differentiate between 1,587 metazoan species. Their results suggested that the region provides efficient taxonomic identification success, and its use was proposed to analyze environmental mixtures (Meusnier et al., 2008); however, the mini-barcode is not variable enough to differentiate between fish species. (Sultana et al., 2018).

Medium-sized (~320 bp) barcodes that are capable of differentiating between fish species have been developed and used in marine metabarcoding studies, and to identify fish species in processed forms. (Shokralla et al., 2015; Collins et al., 2019). Despite the successful use of these markers in fish biodiversity assessment via metabarcoding (Singer et al.,2019; McClenaghan et al., 2020; Russo et al., 2021), biodiversity assessments could be maximized by the use of regional-specific reference barcode libraries (Lin et al., 2020).

In order to better characterize the baselines of Saint Peter and Saint Paul’s fish biodiversity, we collected fishes and generated full barcode sequences. For future metabarcoding monitoring of this region, we constructed a COI reference library of listed fish species from SPSPA, adding our sequences to those previously published. Using this library, we identified a primer pair that would be appropriate to meta-amplify fragmented COI barcodes of SPSPA fishes.

Material and Methods

Five field expeditions were conducted between 2005 and 2015 in surroundings of the Saint Peter and Saint Paul Archipelago (000° 55ʼ N and 029° 21ʼ W; Fig 1). Fishes were opportunistically sampled from authorized longline catches targeting wahoos and tunas (license number SISBIO/ICMBio 014/2005). Muscle fragments were labeled (numbered) and preserved in 96% ethanol at −20°C until their extraction. Sampled fishes were identified following on-site taxonomic guides (Menezes et al., 2003).

DNA was extracted using the PureLink™ Genomic DNA Mini Kit (Thermo Fisher Scientific, Massachusetts, United States) following the manufacturer’s protocol. The forward FishF2 (5′ TCG ACT AAT CAT AAA GAT ATC GGC AC 3′) and reverse FishR2 (5′ ACT TCA GGG TGA CCG AAG AAT CAG AA 3′) primer pair (Ward et al., 2005) was used to amplify the cytochrome c oxidase I (COI) gene by polymerase chain reaction (PCR). Each PCR reaction was conducted in a total volume of 25 μL, consisting of 0.2 mM of dNTPs, buffer 1× 1.5 mM of MgCl2, 0.2 μM of each primer, 1 U of AmpliTaq Gold DNA polymerase (Thermo Fisher Scientific, Massachusetts, United States), 50-100 ng of template DNA quantified using NanoDrop 2000 (Thermo Scientific, Massachusetts, United States), and ultrapure water to a final volume.

The thermal cycling condition began with an initial denaturing at 94 °C for 5 minutes, followed by 35 repeated cycles of denaturing (94 °C for 0.5 minutes), annealing (50 °C for 0.5 min) and extension (72 °C for 1 min), then concluded with a final extension at 72 °C for 7 min. The size and specificity of amplification products were confirmed in 1% agarose gel stained with GelRed (Biotium, Fremont, California). The successful products were purified using exonuclease I and Shrimp Alkaline Phosphatase enzymes (Amersham Biosciences, Little Chalfont, UK). Finally, they were sequenced by the Sanger method on an ABI3730XL DNA sequencer (Thermo Fischer Scientific, Massachusetts, United States) in Macrogen Inc. (Seoul, South Korea), with the forward primer used for amplification.

The sequences were quality checked, and low-quality regions were removed by using the software Geneious Pro version 9 (Biomatters Ltd, Auckland, New Zealand). The removal of chimeric sequences and alignment using ClustalW (Edgar, 2004) were also performed in Geneious software. Species were identified using the “Identification Engine” of the Barcode of Life Data System (BOLD) by selecting ‘Animal Identification (COI)’ and the ‘Species Level Barcode Records’ (accessed 10 June 2021).

The taxonomic identity of each sequence was assigned to the deposited sequence with the highest similarity score. Also, a neighbor-joining tree was constructed based on the aligned dataset using the Kimura 2-Parameter (K2P) model (Kimura, 1980) with 1,000 bootstrap replicates and pairwise deletion in Geneious to cluster candidate species based on their sequences’ similarities.

As the sequenced samples represent only a small fraction of listed Saint Peter and Saint Paul fishes, the names listed in the Pinheiro et al. (2020) study were used to perform a mining within BOLD. Globally distributed COI sequences from the listed species were added to a new SPSPA COI reference database for further reference database expansion. The scientific fish names from the Pinheiro et al. (2020) checklist were searched on the BOLD “Taxonomy Browser” (accessed 15 June 2021). All available COI sequences were subsequently deposited in the SPSPA COI database. A detailed list of specimens and their BOLD IDs is given in Table 1. Then overall mean distance by (K2P) was computed using MEGA X software (Kumar et al., 2018).

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Table 1 -
Sample identification, identified species, their family, similarity to the BOLD database candidate species (%), location of the BOLD matching sequence, deposited sequence (GenBank accession number), and size of the fragment. Identified fishes of Saint Peter and Saint Paul Archipelago.

A new primer pair exclusively curated (based on the physical properties, penalities of hairpin formations and primer-dimers of the SPSPA sequences database) was designed in the Primer3 plugin featured in Geneious Software (Untergasser et al., 2012). The performance of the newly designed primers was tested in silico against Saint Peter and Saint Paul fish sequences repository using the “Add Primers to Sequence” Geneious tool. Among the candidates’ primer pairs, the selected was the one with the highest “Pairwise Identity” targeting all the sequences of the database and with a product size appropriate for future metabarcoding studies.

Results

The first attempt to barcode fishes from SPSPA waters resulted in 28 captured samples, following strict collection rules as a maximum of six fishes could be caught per expedition. The extraction, amplification, and sequencing methods were successful for 26 out of 28 samples (representing 11.55% of the known SPSPA fishes). Among the 26 samples, the COI Barcode could be identified on BOLD with a high percentage of similarity (98.04%-100%; Table 1), revealing 21 species that are found in 11 families of fishes (graphically represented in Figure 2). The sequences were deposited in GenBank under accession numbers OK030800-OK030825. The neighbor-joining tree revealed expected patterns - closely related species in the same genus clustered together while dissimilar species appeared on different branches. Among the 21 species of fish, Canthidermis maculata was the most abundant (three of the samples), followed by Acanthocybium solandri, Xiphias gladius, and Prionace glauca (two samples each). Table 1 also indicates the closest match and where the matching sequence was collected.

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Figure 2-
Neighbor-Joining Tree of the Saint Peter and Saint Paul Archipelago surveyed fish species labeled with substitutions per site.

Of the 21 newly identified fishes, four were not listed in Pinheiro et al. (2020). Those records were then added to a new database. While 165 of the 225 species listed in Pinheiro et al. (2020) have COI sequences deposited in the BOLD database from a fish caught somewhere else, these were also used to complete the database. Therefore, the new Saint Peter and Saint Paul sequence database has 9,183 sequences from 169 species and 63 families of fish. The full reference library can be found at https://github.com/marcelomcruz4/SPSPAfishes. From this species list, 84 are pelagic, 83 are reef-associated or deep-water residents, and two are endemic (Emblemariopsis signifier and Stegastes sanctipauli). The overall mean distance among all sequences was 0.4. Coherently, the AT content was higher than the GC content in the barcoded collected fishes (56.30%), and among the constructed database (AT content: 55.70%).

From this database four new primer pairs were designed. The one with the highest “Pairwise Identity” rate (74.6%) and with the most adequate target size to be amplified is presented below:

SPSPAF-5′ GCTGGAGCATCTGTTGACCT3′,

SPSPAR-5′ CTCCTCCTGCAGGGTCAAAG3′.

This marker is suited to amplify a product size of 262 base pairs from the COI region and performs in silico capacity to amplify 73.6% of Saint Peter and Saint Paul’s sequences.

Discussion

As expected from the revised theory of island biogeography for marine fishes, the SPSPA represents an important reservoir of biological diversity and a refuge for many endemic species that have diversified on these islands through time (Pinheiro et al., 2017). Naturally, the isolation has played a crucial role in the genetic diversity and endemism of the smallest remote tropical island in the world (Luiz et al., 2015). Aside from the distance, seamounts may also have played an essential function in the marine evolution of the SPSPA. The site (as a peak of the mountain range) acted as a “stepping stone” for fishes during successive periods of sea-level changes (Ludt and Rocha, 2015; Dias et al., 2019). Also, the topography and strategic location of the area make it an important feeding and reproduction ground for several migratory pelagic species, mostly with high commercial value (Viana et al., 2015; Macena and Hazin, 2016; Pimentel et al., 2020). Our results confirm the presence of some of these species, such as the blackfin tuna (Thunnus atlanticus), the wahoo (Acanthocybium solandri), the rainbow runner (Elagatis bipinnulata), the flying fishes (Cheilopogon sp.), the silky shark (Carcharhinus falciformis), and the blue shark (Prionace glauca). Due to the heterogeneity of migrants and residents of the region, molecular techniques are a useful tool to catalog and uncover the biodiversity of SPSPA.

DNA Barcoding advantages and limitations

DNA barcoding technology provides an efficient molecular technique for species identification to elucidate global biodiversity (Hebert et al., 2003; Krishnamurthy and Francis, 2012). The mitochondrial COI gene has been barcoding fish species with high efficiency (Ward et al., 2009; Ward, 2012). The marine ichthyofauna was successfully characterized in Australia (Ward et al., 2005), the Antarctic (Rock et al., 2008; Mabragaña et al., 2016), Canada (Steinke et al., 2009), the Arctic (Mecklenburg et al., 2010), Japan (Zhang and Hanner, 2011), India (Lakra et al., 2011), Portugal (Costa et al., 2012), Brazil (Ribeiro et al., 2012), Germany (Knebelsberger et al., 2014), Taiwan (Bingpeng et al., 2018), Indonesia (Limmon et al., 2020), Pakistan (Ghouri et al., 2020), and Bangladesh (Ahmed et al., 2021).

In this unprecedented study, we successfully amplified the COI barcode sequences for Saint Peter and Saint Paul Archipelago fishes. The surveyed site is a remote and protected oceanic island (Soares and Lucas, 2018). This bio-blitz was the first effort to barcode representatives from the SPSPA. To this extent, the sample size is limited and for this reason, the samples of this study were opportunistically collected over different expeditions. Despite these sampling challenges, the COI barcoding genes of 26 fish specimens were successfully amplified and sequenced. The differentiation between species through individual COI barcodes validates the efficiency of COI barcodes for identifying marine fish species.

Even though a complete and robust identification process requires additional steps (such as diagnosable morphological characters and natural history/ecological studies), a DNA bio-scan is an extremely useful method for an initial sorting of new and known biodiversity (Zamani et al., 2022). In this way, our survey opened up the possibility of uncovering the hidden biodiversity of the archipelago.

The feasibility of gathering new species’ records for the region is sustained by the fact that the DNA barcoding revolution has hastened species discovery during the last 15 years (Cao et al., 2016; DeSalle and Goldstein, 2019; Lopez-Vaamonde et al., 2021). In turn, efforts to collect and barcode fish species from specific regions aided new fish records in other regions of the globe, such as Bangladesh, Sri Lanka, and the Bay of Bengal (Rathnasuriya et al., 2019; Ahmed et al., 2021; Sharifuzzaman et al., 2021).

The methodology applied in this study revealed four new records to the Saint Peter and Saint Paul region: Cheilopogon atrisignis; Cheilopogon nigricans; Remora australis; and Thryssa chefuensis. Considering the natural history of these species, it is plausible that Cheilopogon nigricans and Remora australis inhabit the SPSPA, as their distribution is described to be in the neighboring waters of the Atlantic Ocean (Fishbase, 2021). In fact, Remora australis is already photo-documented at SPSPA waters (Hoffmann et al., 2008; Wingert et al., 2021); our survey corroborates the inclusion of this species in future checklists. Whereas Cheilopogon atrisignis and Thryssa chefuensis are related to the Indian and Pacific oceans respectively (Fishbase, 2021). Additional morphometric approaches must be applied in order to confirm the presence of these species in the SPSPA. In particular, the presence of Thryssa chefuensis must be investigated carefully, as there are no other members of the family Engraulidae reported to the archipelago (Pinheiro et al., 2020) and DNA Barcoding has the capacity to detect alien species which invade different ecosystems (Nagarajan et al., 2020).

The identification of two species from the genus Cheilopgon represents new records for the site and confirms the vast diversity of flying fishes in SPSPA. It is reported that at least five species of the genus inhabit the site (Pinheiro et al., 2020); thus, the assignment of Cheilopogon atrisignis or Cheilopogon nigricans could be a case of misidentification due to closely related species with low differentiation between COI sequences. This illustrates one of the limitations of COI barcoding methodologies; i.e., the COI gene is not sufficiently variable to distinguish between some closely related species (Moritz and Cicero, 2004). To overcome this limitation and confirm species identities, more data are needed from morphological characters and/or additional genetic markers.

Future monitoring

DNA Barcoding technical limitations prompted additional research towards the technological transition to Metabarcoding. In other words, to transition from sampling individuals (DNA Barcoding) to whole communities (DNA metabarcoding; Porter and Hajibabaei, 2020). Metabarcoding is a capture-free and non-invasive tool useful for detecting rare, elusive, controlled, protected, or threatened species (Wilcox et al., 2013; Schwentner et al., 2021). With the impossibility to sample individuals from SPSPA, metabarcoding emerges as the solution to survey and monitor SPSPA fish diversity. This approach is becoming a well-established tool for monitoring fishes not only from water samples (Miya, 2022), but also from various types of samples such as air (Lynggaard et al., 2022), sediment (Ip et al., 2021), bottom trawl fishing vessels (Maiello et al., 2022), and feces (Creer et al., 2016; Jarman et al., 2018).

Although the ability to identify and describe new species is limited using COI metabarcoding approaches, the amount of data generated is informative for biodiversity assessment (Taberlet et al., 2018; Meierotto et al., 2019). The collection impediment compromises the construction of a barcode reference database that optimally should be composed only of local specimens (Delrieu-Trottin et al., 2019; Lin et al., 2020). To overcome this limitation, we added to the SPSPA COI reference database COI sequences that were available on BOLD from the listed species but were collected elsewhere. As future metabarcoding steps, the constructed database, as well as the generated primer pair, must be tested in vitro, preferably with SPSPA samples and then directly with SPSPA environmental samples in a pilot study (Taberlet et al., 2018). Another future perspective is the constant update of the SPSPA COI database, this would potentially increase the coverage of endemic species in the database, which currently only has two of the 11 listed endemic species. In this case, collected specimens in the archipelago vouchered in museums, especially the endemic ones, should be barcoded and added to the database (Ward et al., 2009).

Rather than designing primers to target all fishes (Miya et al., 2015; Collins et al., 2019), here we designed primers capable of amplifying fishes found in the target geographical region. We did this by generating an alignment of COI sequences for fishes known to be present in the SPSPA. Fishes are the largest group of vertebrates, and the teleost and elasmobranch species are evolutionarily distant; therefore, their genetic fingerprints are dissimilar (Nelson et al., 2016). We chose to focus on only the fishes of the SPSPA in order to increase the probability of amplification using environmental samples, thus ensuring accurate monitoring and protection.

A cocktail of primers targeting other metabarcodes such as the mitochondrial 12S or 16S rRNA genes (Epp et al., 2012) should be considered for a comprehensive metabarcoding study of the total fish biodiversity of the region (Collins et al., 2019).

Conservation Considerations

Due to the presence and connectivity of key species of corals, crustaceans, mollusks, fishes, marine birds, and cetaceans, SPSPA has been protected by the Ministry of the Environment of Brazil since 1986 (Francini-Filho et al., 2018). Despite the protection, commercial fishing boats were allowed to operate in the SPSPA regularly (Viana et al., 2015). In 2018, the environmental protection of the islands and surroundings was increased by the Brazilian government (Brasil, 2018). However, the vast majority of the new areas are classified as “Areas of Sustainable Use”, where “subsistence” fisheries are specifically allowed in the management plan. In practice, commercial fishing and industrial activities by regional fishing companies are also taking place in these areas, as reported by Giglio et al. (2018). Furthermore, the habitats considered more vulnerable to high environmental impact have not received integral protection. The areas of integral protection were designated in places where these activities are already unlikely or rare (Magris and Pressey, 2018).

Fine-scale geographical and temporal studies are crucial to define boundaries and to set goals for Marine Protected Areas. Therefore, systematic data collection along time and space is necessary to understand the protected ecosystem better and promote possible zoning changes. Considering the richness of SPSPA biodiversity and its lack of protection, advanced genetics tools for monitoring ecosystems are needed. In this case, DNA metabarcoding of marine water has the potential to effectively monitor and give solid periodic information to managers and policymakers (Gold et al., 2021).

Conclusion

The Saint Peter and Saint Paul Archipelago is a reservoir of biodiversity. The strategic location of the archipelago is an important feeding and reproductive ground for a variety of migratory fishes; likewise, it is a refuge to the third-highest fish endemism level in the Atlantic. The checklist of fishes that live in shallow and deep waters has already elucidated these outstanding patterns (Pinheiro et al., 2020); as yet the genetic signatures of SPSPA fish species have remained unknown. Thereupon, this research endeavored to barcode surveyed species of the site and catalog all deposited sequences of listed fishes in the region. Challenges and limitations of the application of DNA Barcoding methodology on SPSPA fishes reveals there is yet more diversity to be discovered. Due to this, the protection of the archipelago should be enhanced and well monitored with more robust approaches. In this case, DNA metabarcoding is an emerging tool that could assist in safeguarding SPSPA fauna; therefore, the reference library and the primer pair specifically designed to study the fishes of these islands should be considered for future metabarcoding monitoring activities.

Acknowledgements

Concerning the samples, the authors would like to express their gratitude to the fishermen of Transmar I and II for their help and their support. This work was funded by the Programa Arquipélago e Ilhas Oceânicas (Grant Number #56/2005, #26/2009, and 39/2012). Also, this work was supported by the Brazilian Navy (SECIRM); Federal University of Rio Grande do Sul (UFRGS); The Brazilian Agency of the Coordination for Improvement of Higher Education Personnel (CAPES); the National Council for Scientific and Technological Development (CNPq), and the Research Support Foundation of the State of Rio Grande do Sul (FAPERGS).

References

  • Ahmed MS, Datta SK, Saha T and Hossain Z (2021) Molecular characterization of marine and coastal fishes of Bangladesh through DNA barcodes. Ecol Evol 11:3696-3709.
  • Berry TE, Saunders BJ, Coghlan ML, Stat M, Jarman S, Richardson AJ, Davies CH, Berry O, Harvey ES and Bunce M (2019) Marine environmental DNA biomonitoring reveals seasonal patterns in biodiversity and identifies ecosystem responses to anomalous climatic events. PLoS Genet 15:e1007943.
  • Bingpeng X, Heshan L, Zhilan Z, Chunguang W, Yanguo W and Jianjun W (2018) DNA barcoding for identification of fish species in the Taiwan Strait. PLoS One 13:e0198109.
  • Blaxter M (2003) Molecular systematics: Counting angels with DNA. Nature 421:122-124.
  • Butchart SH, Walpole M, Collen B, van Strien A, Scharlemann JP, Almond RE, Baillie JE, Bomhard B, Brown C, Bruno J et al (2010) Global biodiversity: Indicators of recent declines. Science 328:1164-1168.
  • Campos TFC, Virgens Neto J, Srivastava NK, Petta RA, Hartmann LA, Moraes JFS, Mendes L and Silveira SRM (2005) Saint Peter and Saint Paul’s Archipelago - Tectonic uplift of infracrustal rocks in the Atlantic Ocean. In: Winge M, Schobbenhaus C, Berbert-Bor M, Queiroz ET, Campos DA, Souza CRG and Fernandes ACS (eds) Geological and palaeontological sites of Brazil. SIGEP, Brasília, pp 1-13.
  • Cao X, Liu J, Chen J, Zheng G, Kuntner M and Agnarsson I (2016) Rapid dissemination of taxonomic discoveries based on DNA barcoding and morphology. Sci Rep 6:37066.
  • Christoffer S and Endre W (2005) What can biological barcoding do for marine biology? Mar Biol Res 1:79-83.
  • Clarke LJ, Soubrier J, Weyrich LS and Cooper A (2014) Environmental metabarcodes for insects: In silico PCR reveals potential for taxonomic bias. Mol Ecol Resour 14:1160-1170.
  • Collins RA, Bakker J, Wangensteen OS, Soto AZ, Corrigan L, Sims DW, Genner MJ and Mariani S (2019) Non‐specific amplification compromises environmental DNA metabarcoding with COI. Methods Ecol Evol 10:1985-2001.
  • Costa FO, Landi M, Martins R, Costa MH, Costa ME, Carneiro M, Alves MJ, Steinke D and Carvalho GR (2012) A ranking system for reference libraries of DNA barcodes: Application to marine fish species from Portugal. PLoS One 7:e35858.
  • Creer S, Deiner K, Frey S, Porazinska D, Taberlet P, Thomas WK, Potter C and Bik HM (2016) The ecologist’s field guide to sequence‐based identification of biodiversity. Methods Ecol Evol 7:1008-1018.
  • Deagle BE, Eveson JP and Jarman SN (2006) Quantification of damage in DNA recovered from highly degraded samples-a case study on DNA in faeces. Front Zool3:11.
  • Delrieu-Trottin E, Williams JT, Pitassy D, Driskell A, Hubert N, Viviani J, Cribb TH, Espiau B, Galzin R, Kulbicki M et al (2019) A DNA barcode reference library of French Polynesian shore fishes. Sci Data 6:114.
  • DeSalle R and Goldstein P (2019) Review and interpretation of trends in DNA barcoding. Front Ecol Evol 7:302.
  • Dias RM, Lima SMQ, Mendes LF, Almeida DF, Paiva PC and Britto MR (2019) Different speciation processes in a cryptobenthic reef fish from the Western Tropical Atlantic. Hydrobiologia 837:133-147.
  • Díaz S, Fargione J, Chapin FS III and Tilman D (2006) Biodiversity loss threatens human well-being. PLoS Biol4:e277.
  • DiBattista JD, Reimer JD, Stat M, Masucci GD, Biondi P, De Brauwer M, Wilkinson SP, Chariton AA and Bunce M (2020) Environmental DNA can act as a biodiversity barometer of anthropogenic pressures in coastal ecosystems. Sci Rep 10:8365.
  • Edgar RC (2004) MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792-1797.
  • Elbrecht V, Braukmann TWA, Ivanova NV, Prosser SWJ, Hajibabaei M, Wright M, Zakharov EV, Hebert PDN and Steinke D (2019) Validation of COI metabarcoding primers for terrestrial arthropods. PeerJ7:e7745.
  • Epp LS, Boessenkool S, Bellemain EP, Haile J, Esposito A, Riaz T, Erséus C, Gusarov VI, Edwards ME, Johnsen A et al (2012) New environmental metabarcodes for analysing soil DNA: Potential for studying past and present ecosystems. Mol Ecol 21:1821-1833.
  • Feitoza BM, Rocha LA, Luis-Júnior OJ, Floeter SR and Gasparini JL (2003) Reef fishes of St. Paul’s Rocks: New records and notes on biology and zoogeography. Aqua7:61-82.
  • Folmer O, Black M, Hoeh W, Lutz R and Vrijenhoek R (1994) DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol Mar Biol Biotechnol3:294-299.
  • Francini-Filho RB, Ferreira CEL, Mello TJ, Prates APL and Silva VN (2018) Diagnóstico biológico e socioeconômico para a proposta de criação de uma Área de Proteção Ambiental (APA) e um Monumento Natural Marinho (MONA) no Arquipélago São Pedro e São Paulo. ICMBio, Brasília.
  • Ghouri MZ, Ismail M, Javed MA, Khan SH, Munawar N, Umar AB, Mehr-un-Nisa, Aftab SO, Amin S, Khan Z et al (2020) Identification of edible fish species of pakistan through DNA barcoding. Front Mar Sci 7:554183
  • Giglio VJ, Pinheiro HT, Bender MG, Bonaldo RM, Lotufo LOC, Ferreira CEL, Floeter SR, Joyeux J-C, Krajewski JP, Gasparini JL et al (2018) Large and remote marine protected areas in the South Atlantic Ocean are flawed and raise concerns: Comments on Soares and Lucas (2018). Mar Policy 96:13-17.
  • Gold Z, Sprague J, Kushner DJ, Marin EZ and Barber PH (2021) eDNA metabarcoding as a biomonitoring tool for marine protected areas. PLoS One 16:e0238557.
  • Hajibabaei M, deWaard JR, Ivanova NV, Ratnasingham S, Dooh RT, Kirk SL, Mackie PM and Hebert PD (2005) Critical factors for assembling a high volume of DNA barcodes. Philos Trans R Soc Lond B Biol Sci 360:1959-1967.
  • Hebert PDN and Gregory TR (2005) The promise of DNA barcoding for taxonomy. Syst Biol 54:852-859.
  • Hebert PDN, Cywinska A, Ball SL and deWaard JR (2003) Biological identifications through DNA barcodes. Proc Biol Sci 270:313-321.
  • Hoffmann LS, Valdez F, Di Tullio J, Fruet P, Caon G, Boherer M and Freitas TRO (2008) Primeiro registro da presença de Remora australis associada aos golfinhos nariz-de-garrafa, Tursiops truncatus, nas águas do entorno do Arquipélago de São Pedro São Paulo, Brasil. In: XIII Reunión de Trabajo de Especialistas en Mamíferos Acuáticos (RT) y 7º Congreso de la Sociedad Latinoamericana de Especialistas en Mamíferos Acuáticos (SOLAMAC), 2008, Montevideo, Uruguay. In XIII Reunión de Trabajo de Especialistas en Mamíferos Acuáticos.
  • Hubert N and Hanner R (2015) DNA Barcoding, species delineation and taxonomy: A historical perspective. DNA Barcodes3:44-58.
  • Ip YCA, Chang JJM, Lim KKP, Jaafar Z, Wainwright BJ and Huang D (2021) Seeing through sedimented waters: environmental DNA reduces the phantom diversity of sharks and rays in turbid marine habitats. BMC Ecol Evol 21:166.
  • Jarman SN, Berry O and Bunce M (2018) The value of environmental DNA biobanking for long-term biomonitoring. Nat Ecol Evol 2:1192-1193.
  • Kimura M (1980) A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol 16:111-120.
  • Knebelsberger T, Landi M, Neumann H, Kloppmann M, Sell AF, Campbell PD, Laakmann S, Raupach MJ, Carvalho GR and Costa FO(2014) A reliable DNA barcode reference library for the identification of the North European shelf fish fauna. Mol Ecol Resour 14:1060-1071.
  • Krishnamurthy P and Francis RA (2012) A critical review on the utility of DNA barcoding in biodiversity conservation. Biodivers Conserv 21:1901-1919.
  • Kumar S, Stecher G, Li M, Knyaz C and Tamura K (2018) MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 35:1547-1549.
  • Lakra WS, Verma MS, Goswami M, Lal KK, Mohindra V, Punia P, Gopalakrishnan A, Singh KV, Ward RD, and Hebert P (2011) DNA barcoding Indian marine fishes. Mol Ecol Resour 1160-71.
  • Limmon G, Delrieu-Trottin E, Patikawa J, Rijoly F, Dahruddin H, Busson F, Steinke D and Hubert N (2020) Assessing species diversity of Coral Triangle artisanal fisheries: A DNA barcode reference library for the shore fishes retailed at Ambon harbor (Indonesia). Ecol Evol 10:3356-3366.
  • Lin XL, Mo L, Bu WJ and Wang XH (2020) The first comprehensive DNA barcode reference library of Chinese Tanytarsus (Diptera: Chironomidae) for environmental DNA metabarcoding. Divers Distrib 27:1932-1941.
  • Lopez-Vaamonde C, Kirichenko N, Cama A, Doorenweerd C, Godfray HCJ, Guiguet A, Gomboc S, Huemer P, Landry JF, Laštůvka A et al (2021) Evaluating DNA barcoding for species identification and discovery in European gracillariid moths. Front Ecol Evol 9:626752.
  • Lubbock R and Edwards A (1981) The fishes of Saint Paul’s Rocks. J Fish Biol 18:135-157.
  • Ludt WB and Rocha LA (2015) Shifting seas: The impacts of Pleistocene sea-level fluctuations on the evolution of tropical marine taxa. J Biogeogr 42:25-38.
  • Luiz OJ, Mendes TC, Barneche DR, Ferreira CGW, Noguchi R, Villaça RC, Rangel CA, Gasparini JL and Ferreira CEL (2015) Community structure of reef fishes on a remote oceanic island (St Peter and St Paul’s Archipelago, equatorial Atlantic): The relative influence of abiotic and biotic variables. Mar Freshw Res 66:739-749.
  • Lynggaard C, Bertelsen MF, Jensen CV, Johnson MS, Frøslev TG, Olsen MT and Bohmann K (2022) Airborne environmental DNA for terrestrial vertebrate community monitoring. Curr Biol 32:701-707.
  • Mabragaña E, Delpiani SM, Rosso JJ, González-Castro M, Antoni MD, Hanner R and Astarloa JMD (2016) Barcoding antarctic fishes: Species discrimination and contribution to elucidate ontogenetic changes in nototheniidae. In: Trivedi S, Ansari A, Ghosh S and Rehman H (eds) DNA barcoding in marine perspectives. Springer, Cham, pp 213-242.
  • Macena BCL and Hazin FHV (2016) Whale shark (Rhincodon typus) seasonal occurrence, abundance and demographic structure in the mid-equatorial atlantic ocean. PLoS One 11:e0164440.
  • Magris RA and Pressey RL (2018) Marine protected areas: Just for show? Science 360:723-724.
  • Maiello G, Talarico L, Carpentieri P, De Angelis F, Franceschini S, Harper LR, Neave EF, Rickards O, Sbrana A, Shum P et al (2022) Little samplers, big fleet: eDNA metabarcoding from commercial trawlers enhances ocean monitoring. Fish Res 249:106259.
  • McClenaghan B, Fahner N, Cote D, Chawarski J, McCarthy A, Rajabi H, Singer G and Hajibabaei M (2020) Harnessing the power of eDNA metabarcoding for the detection of deep-sea fishes. PLoS One 15:e0236540.
  • Mecklenburg CW, Møller PR and Steinke D (2010) Biodiversity of arctic marine fishes: Taxonomy and zoogeography. Mar Biodiv 41:109-140.
  • Meierotto S, Sharkey MJ, Janzen DH, Hallwachs W, Hebert PDN, Chapman EG and Smith MA (2019) A revolutionary protocol to describe understudied hyperdiverse taxa and overcome the taxonomic impediment. Mitt Mus Naturkunde Berl Dtsch Entomol Z 66:119-145.
  • Mendonça SA, Macena BCL, Afonso AS and Hazin FHV (2018) Seasonal aggregation and diel activity by the sicklefin devil ray Mobula tarapacana off a small, equatorial outcrop of the Mid-Atlantic Ridge. J Fish Biol 93:1121-1129.
  • Menezes NA, Buckup PA, Figueiredo JL and Moura RL (2003) Catálogo das espécies de peixes marinhos do Brasil. Museu de Zoologia USP, São Paulo, 160 p.
  • Meusnier I, Singer GA, Landry J-F, Hickey DA, Hebert PD and Hajibabaei M (2008) A universal DNA mini-barcode for biodiversity analysis. BMC Genomics 9:214.
  • Miya M, Sato Y, Fukunaga T, Sado T, Poulsen JY, Sato K, Minamoto T, Yamamoto S, Yamanaka H, Araki H I et al (2015) MiFish, a set of universal PCR primers for metabarcoding environmental DNA from fishes: Detection of more than 230 subtropical marine species. R Soc Open Sci 2:150088.
  • Miya M (2022) Environmental DNA metabarcoding: A novel method for biodiversity monitoring of marine fish communities. Ann Rev Mar Sci 14:161-185.
  • Mohriak WU (2020) Genesis and evolution of the South Atlantic volcanic islands offshore Brazil. Geo-Mar Lett 40:1-33.
  • Moritz C and Cicero C (2004) DNA barcoding: Promise and pitfalls. PLoS Biol 2:e354.
  • Nagarajan M, Parambath A and Prabhu V (2020) DNA barcoding: A potential tool for invasive species identification. In: Trivedi S, Rehman H, Saggu S, Panneerselvam C and Ghosh S (eds) DNA barcoding and molecular phylogeny. Springer, Cham , pp 31-43.
  • Nelson JS, Grande TC and Wilson MV (2016) Fishes of the world. 5th edition. John Wiley & Sons, Hoboken, 752 p.
  • Ogwang J, Bariche M and Bos AR (2020) Genetic diversity and phylogenetic relationships of threadfin breams (Nemipterus spp.) from the Red Sea and eastern Mediterranean Sea. Genome 64:207-216.
  • Pimentel CR, Andrades R, Ferreira CEL, Gadig OBF, Harvey ES, Joyeux J-C and Giarrizzo T (2020) BRUVS reveal locally extinct shark and the way for shark monitoring in Brazilian oceanic islands. J Fish Biol 96:539-542.
  • Pinheiro HT, Bernardi G, Simon T, Joyeux JC, Macieira RM, Gasparini JL, Rocha C and Rocha LA (2017) Island biogeography of marine organisms. Nature 549:82-85.
  • Pinheiro HT, Macena BCL, Francini-Filho RB, Ferreira CEL, Albuquerque FV, Bezerra N, Carvalho-Filho A, Ferreira RCP, Luiz OJ, Mello TJ et al (2020) Fish biodiversity of Saint Peter and Saint Paul’s Archipelago, Mid-Atlantic Ridge, Brazil: New records and a species database. J Fish Biol 97:1143-1153.
  • Pinsky ML, Eikeset AM, McCauley DJ, Payne JL and Sunday JM (2019) Greater vulnerability to warming of marine versus terrestrial ectotherms. Nature 569:108-111.
  • Porter T and Hajibabaei M (2020) Putting COI metabarcoding in context: The utility of Exact Sequence Variants (ESVs) in biodiversity analysis. Front Ecol Evol 8, 248.
  • Rathnasuriya MIG, Mateos-Rivera A, Bandara AGGC, Skern-Mauritzen R, Jayasnghe RPPK, Krakstad JO and Dalpadado P (2019) DNA barcoding confirms the first record of a Desmodema polystictum (Ogilby, 1898) egg and all-time high adult catches in the Indian Ocean. Mar Biodivers Rec 12:22.
  • Ribeiro AO, Caires RA, Mariguela TC, Pereira LHG, Hanner R and Oliveira C (2012) DNA barcodes identify marine fishes of São Paulo State, Brazil. Mol Ecol Resour 12:1012-1020.
  • Rock J, Costa FO, Walker DI, North AW, Hutchinson WF and Carvalho GR (2008) DNA barcodes of fish of the Scotia Sea, Antarctica indicate priority groups for taxonomic and systematics focus. Antarct Sci 20:253-262.
  • Russo T, Maiello G, Talarico L, Baillie C, Colosimo G, D’Andrea L, Di Maio F, Fiorentino F, Franceschini S, Garofalo G et al (2021) All is fish that comes to the net: Metabarcoding for rapid fisheries catch assessment. Ecol Appl 31:e02273.
  • Schwentner M, Zahiri R, Yamamoto S, Husemann M, Kullmann B and Thiel R (2021) eDNA as a tool for non-invasive monitoring of the fauna of a turbid, well-mixed system, the Elbe estuary in Germany. PLoS One 16:e0250452.
  • Sharifuzzaman SM, Rasid MH, Rubby IA, Debnath SC, Xing B, Chen G, Chowdhury MSN and Hossain MS (2021) DNA barcoding confirms a new record of flyingfish Cheilopogon spilonotopterus (Beloniformes: Exocoetidae) from the northern Bay of Bengal. Conserv Genet Resour 13:323-328.
  • Shokralla S, Hellberg RS, Handy SM, King I and Hajibabaei M (2015) A DNA Mini-Barcoding system for authentication of processed fish products. Sci Rep 5:15894.
  • Singer GAC, Fahner NA, Barnes JG, McCarthy A and Hajibabaei M (2019) Comprehensive biodiversity analysis via ultra-deep patterned flow cell technology: A case study of eDNA metabarcoding seawater. Sci Rep 9:5991.
  • Soares MO and Lucas CC (2018) Towards large and remote protected areas in the South Atlantic Ocean: St. Peter and St. Paul´s Archipelago and the Vitória-Trindade Seamount Chain. Mar Policy 93:101-103.
  • Stat M, Huggett MJ, Bernasconi R, DiBattista JD, Berry TE, Newman SJ, Harvey ES and Bunce M (2017) Ecosystem biomonitoring with eDNA: Metabarcoding across the tree of life in a tropical marine environment. Sci Rep7:12240.
  • Steinke D, Zemlak TS, Boutillier JA and Hebert PDN (2009) DNA barcoding of Pacific Canada’s fishes. Mar Biol 156:2641-2647.
  • Sultana S, Ali ME, Hossain MAM, Naquiah N and Zaidul ISM (2018) Universal mini COI barcode for the identification of fish species in processed products. Food Res Int 105:19-28.
  • Taberlet P, Bonin A, Zinger L and Coissac E (2018) Environmental DNA: For biodiversity research and monitoring. Oxford University Press, Oxford, 253 pp.
  • Taberlet P, Coissac E, Hajibabaei M and Rieseberg LH (2012) Environmental DNA. Mol Ecol 21:1789-1793.
  • Thomsen PF and Willerslev E (2015) Environmental DNA - an emerging tool in conservation for monitoring past and present biodiversity. Biol Conserv 183:4-18.
  • Untergasser A, Cutcutache I, Koressaar T, Ye J, Faircloth BC, Remm M and Rozen SG (2012) Primer3--new capabilities and interfaces. Nucleic Acids Res 40:e115.
  • Vaske TJ, Lessa RP, de Nóbrega M, Montealegre-Quijano S, Marcante SF and Bezerra JLJ (2005) A checklist of fishes from Saint Peter and Saint Paul Archipelago, Brazil. J Appl Ichthyol 21:75-79.
  • Viana D, Hazin F and Souza MO (2009) Arquipélago de São Pedro e São Paulo: 10 anos de estação científica. SECIRM, Brasília, 348pp.
  • Viana D, Hazin F, Andrade H, Nunes D and Viana D (2015) Fisheries in the Saint Peter and Saint Paul archipelago: 13 years of monitoring. B Inst Pesca 41:239-248.
  • Wangensteen OS, Palacín C, Guardiola M and Turon X (2018) DNA metabarcoding of littoral hard-bottom communities: High diversity and database gaps revealed by two molecular markers. PeerJ 6:e4705.
  • Ward RD (2012) FISH-BOL, a case study for DNA barcodes. Methods Mol Biol 858:423-439.
  • Ward RD, Hanner R and Hebert PDN (2009) The campaign to DNA barcode all fishes, FISH-BOL. J Fish Biol 74:329-356.
  • Ward RD, Zemlak TS, Innes BH, Last PR and Hebert PDN (2005) DNA barcoding Australia’s fish species. Philos Trans R Soc Lond B Biol Sci 360:1847-1857.
  • Wilcox TM, McKelvey KS, Young MK, Jane SF, Lowe WH, Whiteley AR and Schwartz MK (2013) Robust detection of rare species using environmental DNA: The importance of primer specificity. PLoS One 8:e59520.
  • Wingert N, Milmann L, Baumgarten M, Danilewicz D, Sazima I and Ott P (2021) Relationships between common Bottlenose Dolphins (Tursiops truncatus) and Whalesuckers (Remora australis) at a remote archipelago in the Equatorial Atlantic Ocean. Aquat Mamm 47:585-598.
  • Yu DW, Ji Y, Emerson BC, Wang X, Ye C, Yang C and Ding Z (2012) Biodiversity soup: Metabarcoding of arthropods for rapid biodiversity assessment and biomonitoring. Methods Ecol Evol3:613-623.
  • Zamani A, Fric ZF, Gante HF, Hopkins T, Orfinger AB, Scherz MD, Bartonová AS and Pos DD (2022) DNA barcodes on their own are not enough to describe a species. Syst Entomol 47:3385-389.
  • Zhang J and Hanner R (2011) DNA barcoding is a useful tool for the identification of marine fishes from Japan. Biochem Syst Ecol39:31-42.

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Edited by

  • Associate Editor:
    Antonio Matteo Solé-Cava

Publication Dates

  • Publication in this collection
    03 Oct 2022
  • Date of issue
    2022

History

  • Received
    28 Oct 2021
  • Accepted
    04 Aug 2022
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