DNA barcoding and metabarcoding of standardized samples reveal patterns of marine benthic diversity.

Only 10% of the earth’s biota has been described despite250 yearsoftaxonomicresearch(Wilson2000).Thisisinlargepart a reflection of the extent and complexity of biologicaldiversity,butitisalsotruethattraditionaltaxonomictechniquesare labourious and highly specialised, and taxonomic expertiseis very thinly spread across the myriad groups of life (Scotland

AimDNA metabarcoding has great potential to improve biomonitoring in island's marine ecosystems, which are highly vulnerable to global change and non‐indigenous species (NIS) introductions. However, the depth and accuracy of the taxonomic identifications are mainly dependent on reference libraries containing representative and reliable sequences for the targeted species. In this study, we evaluated the gaps in the availability of DNA sequences and their accuracy for macroinvertebrates inhabiting Macaronesia's shallow marine habitats.LocationMacaronesia (Azores, Madeira, Selvagens, Canaries).MethodsChecklists of marine invertebrates occurring above 50 m depth were compiled using public databases and published checklists. The availability of cytochrome c oxidase subunit I (COI) and 18S rRNA (18S) gene sequences was verified in BOLD and GenBank. Finally, COI data were audited to check the congruence between morphospecies and Barcode Index Numbers (BINs).ResultsThe taxonomic coverage of different phyla was greater for COI but unbalanced and variable among archipelagos. NIS were better represented in genetic databases (up to 73% and 59%, for COI and 18S, respectively) than native species (up to 47% and 31%, for COI and 18S, respectively). NIS displayed a higher number of discordant records, and native species, a higher quantity of cases of multiple BINs. Notably, DNA sequences generated from specimens collected from Macaronesia were found in less than 10% of the species. Projection of the rates of accretion of DNA sequences suggests that decades will be needed to complete these reference libraries.Main conclusionsThe level of completion of reference libraries for Macaronesia's marine macroinvertebrates is generally poor. Without a solid effort to speed up the production of sequence data (i.e. generate more DNA barcodes), the ability to employ DNA‐based biomonitoring of such vulnerable fauna is compromised. The high levels of suspected hidden diversity further deepen the expected gaps and reinforce the vulnerability of this endemism‐rich fauna.

Traditionally, community ecologists assumed that spe-cies differ in some aspects of their traits or responsesto the environment (i.e. their niches), which allow themto coexist in the same habitat (Hutchinson 1957, 1959).Recently, Hubbell (2001) and others (e.g. Bell 2001,2003) have suggested that this view is inadequate toexplain the diversity often observed in speciose systems.For example, hundreds to thousands of tree species livein tropical forests, which only have a handful of limitingresources such as water, light, and a variety of macro- andmicronutrients. Such high diversity, with so few resources,they argue, cannot be explained by niche theory.As an alternative to the traditional niche theory,Hubbell (2001) developed a neutral theory of commu-nity structure (see also Caswell 1976; Hubbell 1979;Hubbell & Foster 1986; Bell 2000, 2001, 2003; Chave L Chave 2004). In the neutral theory, pat-terns of species diversity, relative abundance, andcomposition are primarily a function of the size of themetacommunity, the dispersal rate of organisms withinthe metacommunity, and the rates of generation (spe-ciation) of new species (Bell 2001; Hubbell 2001; Chave2004). Because species are assumed to be identicalecologically, Hubbell termed his a ‘neutral theory’, bydirect analogy to neutral genes in population genetics.Hubbell further termed his theory ‘unified’ in that it issimultaneously able to predict diversity and relativeabundance of organisms in a locality, as well as bioge-ographic patterns of species composition.In this essay, I overview the key assumptions (inputs)required and the insights (outputs) that can be gainedfrom each framework. While a complete discussion ofall of the assumptions and predictions of these modelsis beyond the scope of this essay (but see Chase

Recent advances in environmental DNA‐based biodiversity assessment and conservation

Oomycete species occupy many different environments and many ecological niches. The genera Phytophthora and Pythium for example, contain many plant pathogens which cause enormous damage to a wide range of plant species. Proper identification to the species level is a critical first step in any investigation of oomycetes, whether it is research driven or compelled by the need for rapid and accurate diagnostics during a pathogen outbreak. The use of DNA for oomycete species identification is well established, but DNA barcoding with cytochrome c oxidase subunit I (COI) is a relatively new approach that has yet to be assessed over a significant sample of oomycete genera. In this study we have sequenced COI, from 1205 isolates representing 23 genera. A comparison to internal transcribed spacer (ITS) sequences from the same isolates showed that COI identification is a practical option; complementary because it uses the mitochondrial genome instead of nuclear DNA. In some cases COI was more discriminative than ITS at the species level. This is in contrast to the large ribosomal subunit, which showed poor species resolution when sequenced from a subset of the isolates used in this study. The results described in this paper indicate that COI sequencing and the dataset generated are a valuable addition to the currently available oomycete taxonomy resources, and that both COI, the default DNA barcode supported by GenBank, and ITS, the de facto barcode accepted by the oomycete and mycology community, are acceptable and complementary DNA barcodes to be used for identification of oomycetes.

Objective To make up the limitations of traditional morphological classification methods, we identified vector fleas by DNA barcoding in Qinghai Province. Methods The mt DNA cytochrome c oxidase subunit Ⅰ(COⅠ) gene was amplified by PCR from 36 muscle tissues of fleas in 3 states, 2 cities and 5 counties of Qinghai Province, and the obtained COⅠ gene fragments were sequenced and aligned. The intra- and inter-species genetic distances were calculated with Mega 6 software using K2-P model and a phylogenetic tree was constructed with neighbor-joining (NJ) method. Results Totally 36 COⅠ gene sequences of 2 superfamilies, 4 genera and 6 kinds of vector fleas were measured, the average genetic distance was 0.119, and the intraspecific distance was 0.002 - 0.027, the interspecific distance was 0.039 - 0.207, and the interspecific genetic distance was significantly greater than the intraspecific genetic distance. NJ tree showed the same species had formed a single line with high support rate and interspecific branch was clear. Conclusion DNA barcoding is suitable for identification of vector fleas in Qinghai Province, may make up the limitations of traditional morphological classification methods. Key words: Siphonaptera; Cytochrome c oxidase subunit Ⅰ; DNA barcoding

DNA barcoding is a novel concept for the taxonomic identification, in that it uses a specific short genetic marker in an organism’s DNA to discriminate species. In 2003, professor Paul D. N. Hebert, “the father of DNA barcoding”, of the University of Guelph, Ontario, Canada first proposed the idea to identify biological species using DNA barcode, where the mitochondrial gene cytochrome c oxidase subunit I (COI) was supposed to be the first candidate for animals (Hebert et al. 2003a). Their studies of COI profiling in both higher taxonomic categories and species-level assignment demonstrated that COI gene has significant resolutions across the animal kingdom except the phylum Cnidaria (Hebert et al. 2003b, Ward et al. 2005, Hajibabaei et al. 2006). From then on, a wide broad of taxonomic groups (i.e. birds, fish, butterflies, spiders, ants, etc) were examined by COI gene for its usability as the barcode (i.e. Hebert et al. 2004a, Hebert et al. 2004b, Greenstone et al. 2005, Smith et al. 2005, Barber and Boyce 2006, Meier et al. 2006, Kerr et al. 2007, Kumar et al. 2007, Pfenninger et al. 2007, Stahls and Savolainen 2008, Zhou et al. 2009). Meanwhile, other candidate genes, including Internal Transcribed Spacer (ITS), trnH-psbA intergenic spacer (trnH-psbA), Ribulose-bisphosphate carboxylase (rbcL) and Maturase K (matK) were analysed by different research groups (Jaklitsch et al. 2006, Evans et al. 2007, Ran et al. 2010, de Groot et al. 2011, Liu et al. 2011, Piredda et al. 2011, Yesson et al. 2011). Till recently, there are about 30 DNA barcode candidates are tested, and 4 to 8 of them are widely used for the identification of diversified taxonomic groups with a relatively good resolution. It has been estimated that there are 10 to 100 million species of living creatures in the earth, while what we know is very limited. Knowing the biodiversity is one of the crucial biological issues of ecology, evolutionary biology, bio-security, agro-biotechnology, bioresources and many other areas. For very long period, taxonomists have provided a nomenclatural hierarchy and key prerequisites for the society. However, the needs for species identification requested by non-taxonomists require the knowledge held by taxonomists. Therefore, a standardized, rapid and inexpensive species identification approach is needed to establish for the non-specialists. There had some attempts on the molecular identification systems based on polymerase chain reaction (PCR), especially in bacterial studies (Woese 1996, Zhou et al. 1997, Maiden et al. 1998, Wirth et al. 2006), but no successful solutions for broader scopes of eukaryotes (reviewed in Frezal and Leblois 2008). The DNA Barcode of Life project is another attempt to create a universal eukaryotic identification system based on molecular approaches. Following studies by Hebert et al.

Ambiguities within species description and identification may compromise research validity. Species identification has typically been based upon morphological characteristics, yet recent technological advances have led to identifications achieved via DNA approaches, including DNA barcoding. DNA barcoding studies typically use cytochrome c oxidase subunit I (COI) as the proposed universal molecular marker for animals. Here, we test 12 mitochondrial protein coding genes for the presence of a clear barcoding gap allowing us to unequivocally define species. Using the African Great Apes as our model group, we assess this at the species (Pan troglodytes), genus (Pan) and family (Hominidae) level. Based on 279 complete mitochondrial genomes, sequences were partitioned by gene for analysis and pairwise distances were calculated. No barcoding gap was observed at the within species level, i.e., the four recognised chimpanzee taxa were not distinguishable through DNA barcoding. However, NADH dehydrogenase subunit 5 (ND5) and cytochrome c oxidase subunit II (COII) produce the largest barcoding gaps at the genus (ND5 2%, COII 0.5%) and family (ND5 1.5%, COII 0.5%) level. Rather than focusing on COI, our analysis suggests that these two genes may be more, or at least as, appropriate markers in primate species delineation, with uses in the identification of extinct and extant species. Further use may be beneficial to taxonomists, providing additional evidence and new insights for these morphologically similar species.

Context Acarina are commonly collected in macroinvertebrate surveys used to monitor freshwater ecosystems. However, they can be difficult to identify morphologically requiring considerable taxonomic skill for identification to finer taxonomic levels. Therefore, in biomonitoring they are identified to subclass despite high species diversity and varied environmental responses. DNA barcoding individuals and DNA metabarcoding of bulk samples enables species to be accurately and routinely identified. However, poor DNA barcode coverage of Australian aquatic mites has hampered their use in DNA studies. Aims Here, we aim to generate DNA barcodes for mites from Greater Melbourne, Australia. Key results For many specimens, we link DNA barcodes to genus-level morphological identifications using genetic analysis of DNA barcodes to understand biodiversity. We then test if new DNA barcodes can improve identification of mites in samples processed with DNA metabarcoding. We found Australian aquatic mites showed high diversity with many DNA barcodes represented by single specimens. Conclusions Increased mite DNA barcode library coverage improved their detection using DNA metabarcoding. Implications Given high species diversity, much effort will be required to improve DNA barcode coverage for aquatic mites in Australia and integrate barcodes with species level taxonomy, allowing Acarina to be better incorporated into DNA-based biological monitoring.

Metabarcoding extra‐organismal DNA from environmental samples is now a key technique in aquatic biomonitoring and ecosystem health assessment. Of critical consideration when designing experiments, and especially so when developing community standards and legislative frameworks, is the choice of genetic marker and primer set. Mitochondrial cytochrome c oxidase subunit I (COI), the standard DNA barcode marker for animals, with its extensive reference library, taxonomic discriminatory power and predictable sequence variation, is the natural choice for many metabarcoding applications. However, for targeting specific taxonomic groups in environmental samples, the utility of COI has yet to be fully scrutinized. Here, by using a case study of marine and freshwater fishes from the British Isles, we quantify the in silico performance of twelve primer pairs from four mitochondrial loci – COI, cytochrome b, 12S and 16S – in terms of reference library coverage, taxonomic discriminatory power and primer universality. We subsequently test in vitro four primer pairs – three COI and one 12S – for their specificity, reproducibility, and congruence with independent datasets derived from traditional survey methods at five estuarine and coastal sites around the English Channel and North Sea. Our results show that for aqueous extra‐organismal DNA at low template concentrations, both metazoan‐targeted and fish‐targeted COI primers perform poorly in comparison to 12S, exhibiting low levels of reproducibility due to non‐specific amplification of prokaryotic and non‐target eukaryotic DNAs. An ideal metabarcode would have an extensive reference library upon which custom primers could be designed, either for broad assessments of biodiversity, or taxon specific surveys. Such a database is available for COI, but low primer specificity hinders practical application, while conversely, 12S primers offer high specificity, but lack adequate references. The latter, however, can be mitigated by expanding the concept of DNA barcodes to include whole mitochondrial genomes generated by genome‐skimming existing tissue collections.

Abstract. Djoemharsjah IS, Ambarwati R, Rahayu DA. 2023. DNA barcoding Clithonsp. (Gastropoda: Neritidae) from Badur Beach, Madura, Indonesia, based on COI gene molecular marker. Biodiversitas 24: xxxx. Neritidae is polymorphic with various shell colors and patterns; therefore, they were doubts about the identifying species from the genus Clithon, namely Clithon sp. from Badur Beach of Madura Island, Sumenep District, East Java Province, Indonesia. In addition, DNA barcoding could provide genetic information using short DNA sequences to quickly and precisely identify species. This study aimed to identify the genus Clithon sp. from Badur Beach, based on Cytochrome Oxidase subunit I(COI) genes and analysis of phylogenetic relationships. The research methods include sampling, sample preservation, morphological identification of species, DNA isolation, amplification, electrophoresis, and sequencing using the Sanger method with genetic analysis using bioinformatics software. The results of COI barcode identification obtained a DNA sequence length of 490bp with a similarity value of the three Clithon sp. samples between 96.75 to 98.97%. The identification with the Barcode of Life Data System consisted of three variations of nucleotide bases, and the average value of the genetic distance with the in-group was 1.74% as Clithon sp. The Phylogenetic tree Clithon sp. from Badur Beach, was in the same clade as Clithon sowerbianum Récluz 1843 and Clithon mertonianum Récluz 1843 with the Neighbor-Joining Tree and Maximum Likelihood methods with bootstrap values between 96-100. Therefore, the COI barcode DNA markers analysis successfully identified Clithon sp. from Badur Beach, Madura, Indonesia as C. sowerbianum.

Essential fish habitat is critical for foraging, breeding, or as refugia. As such, restoration of these habitats has the potential to increase the diversity and abundance of fishes. Here, we explored how fish communities responded in the first 12-24 mo following oyster reef restoration. Study sites included 8 restored reefs plus 4 live and 4 dead reefs as controls. Oyster reef metrics (e.g. density, height, thickness) and fish abundance and diversity metrics were quantified, including species richness, Shannon diversity, Simpson’s diversity, and Pielou’s evenness. Species composition was explored further to identify indicator species and assess habitat preferences. Patterns of fish community diversity and species composition were compared to oyster reef metrics to discern what oyster reef characteristics best predict fish diversity. Results showed that intertidal oyster reefs were structurally restored and shifted from resembling negative control reefs to positive control reefs within 12-24 mo. Across all treatment types, oyster shell height and reef thickness were the best predictors of fish diversity. However, at the fish community level, assemblages at restored reefs were similar to those at positive and negative controls. Species-level analyses suggest treatment types have unique indicator species, including Chilomycterus schoepfi (striped burrfish) for dead reefs, Lutjanus synagris (lane snapper) for restored reefs, and Gobiosoma robustum (code goby) for live reefs. This work suggests fishes can be used as higher trophic level indicators of restoration success, and ecosystem-based approaches, such as habitat restoration, can restore essential fish habitat, thus benefiting fish communities while moving coastal ecosystems toward sustainability.

DNA barcoding technology has become employed widely for biodiversity and molecular biology researchers to identify species and analyze their phylogeny. Recently, DNA metabarcoding and environmental DNA (eDNA) technology have developed by expanding the concept of DNA barcoding. These techniques analyze the diversity and quantity of organisms within an environment by detecting biogenic DNA in water and soil. It is particularly popular for monitoring fish species living in rivers and lakes (Takahara et al. 2012). BOLD Systems (Barcode of Life Database systems, Ratnasingham and Hebert 2007) is a database for DNA barcoding, archiving 8.5 million of barcodes (as of August 2020) along with the voucher specimen, from which the DNA barcode sequence is derived, including taxonomy, collected country, and museum vouchered as metadata (e.g. https://www.boldsystems.org/index.php/Public_RecordView?processid=TRIBS054-16). Also, many barcoding data are submitted to GenBank (Sayers et al. 2020), which is a database for DNA sequences managed by NCBI (National Center for Biotechnology Information, US). The number of the records of DNA barcodes, i.e. COI (cytochrome c oxidase I) gene for animal, has grown significantly (Porter and Hajibabaei 2018). BOLD imports DNA barcoding data from GenBank, and lots of DNA barcoding data in GenBank are also assigned BOLD IDs. However, we have to refer to both BOLD and GenBank data when performing DNA barcoding. I have previously investigated the registration of DNA barcoding data in GenBank, especially the association with BOLD, using insects and flowering plants as examples (Nakazato 2019). Here, I surveyed the number of species covered by BOLD and GenBank. I used fish data as an example because eDNA research is particularly focused on fish. I downloaded all GenBank files for vertebrates from NCBI FTP (File Transfer Protocol) sites (as of November 2019). Of the GenBank fish entries, 86,958 (7.3%) were assigned BOLD identifiers (IDs). The NCBI taxonomy database has registrations for 39,127 species of fish, and 20,987 scientific names at the species level (i.e., excluding names that included sp., cf. or aff.). GenBank entries with BOLD IDs covered 11,784 species (30.1%) and 8,665 species-level names (41.3%). I also obtained whole "specimens and sequences combined data" for fish from BOLD systems (as of November 2019). In the BOLD, there are 273,426 entries that are registered as fish. Of these entries, 211,589 BOLD entries were assigned GenBank IDs, i.e. with values in “genbank_accession” column, and 121,748 entries were imported from GenBank, i.e. with "Mined from GenBank, NCBI" description in "institution_storing" column. The BOLD data covered 18,952 fish species and 15,063 species-level names, but 35,500 entries were assigned no species-level names and 22,123 entries were not even filled with family-level names. At the species level, 8,067 names co-occurred in GenBank and BOLD, with 6,997 BOLD-specific names and 599 GenBank-specific names. GenBank has 425,732 fish entries with voucher IDs, of which 340,386 were not assigned a BOLD ID. Of these 340,386 entries, 43,872 entries are registrations for COI genes, which could be candidates for DNA barcodes. These candidates include 4,201 species that are not included in BOLD, thus adding these data will enable us to identify 19,863 fish to the species level. For researchers, it would be very useful if both BOLD and GenBank DNA barcoding data could be searched in one place. For this purpose, it is necessary to integrate data from the two databases. A lot of biodiversity data are recorded based on the Darwin Core standard while DNA sequencing data are sometimes integrated or cross-linked by RDF (Resource Description Framework). It may not be technically difficult to integrate these data, but the species data referenced differ from the EoL (The Encyclopedia of Life) for BOLD and the NCBI taxonomy for GenBank, and the differences in taxonomic systems make it difficult to match by scientific name description. GenBank has fields for the latitude and longitude of the specimens sampled, and Porter and Hajibabaei 2018 argue that this information should be enhanced. However, this information may be better described in the specimen and occurrence databases. The integration of barcoding data with the specimen and occurrence data will solve these problems. Most importantly, it will save the researcher from having to register the same information in multiple databases. In the field of biodiversity, only DNA barcode sequences may have been focused on and used as gene sequences. The museomics community regards museum-preserved specimens as rich resources for DNA studies because their biodiversity information can accompany the extraction and analysis of their DNA (Nakazato 2018). GenBank is useful for biodiversity studies due to its low rate of mislabelling (Leray et al. 2019). In the future, we will be working with a variety of DNA, including genomes from museum specimens as well as DNA barcoding. This will require more integrated use of biodiversity information and DNA sequence data. This integration is also of interest to molecular biologists and bioinformaticians.

Trombiculid mites (Acariformes) are unique among arthropods of medical importance in that only the larval instar (chigger) is parasitic, which can result in the transmission of zoonotic scrub typhus. The use of molecular approaches for chigger species discrimination has been very limited until recently, especially for those parasitizing bird hosts, where data remain scarce. Here, we aimed to generate DNA barcodes of chiggers parasitizing birds in Malaysia based on the mitochondrial cytochrome c oxidase subunit I (COI) gene following DNA extraction, PCR and sequencing. Fifty-four COI sequences from 8 bird-associated chigger species in Malaysia were combined with 50 GenBank sequences comprising 7 genera from various countries for DNA barcode and phylogenetic analysis. The correct identification rates for the 95 COI barcodes were 96.84% (Best Match) and 86.31% (Best-Close Match). DNA barcode analyses effectively clustered the 8 nominal species from this study into their respective genera. Genetic divergence of less than 3% was observed within Ascoschoengastia lorius, Neoschoengastia gallinarum, Parascoschoengastia heynemani, Leptotrombidium imphalum, and Blankaartia acuscutellaris, all of which formed a monophyletic clade, confirming their conspecific nature. Conversely, intraspecific divergences of 17.64%, 15.49%, and 11.63% were obtained for Toritrombicula densipiliata, Odontacarus audyi, and Leptotrombidium deliense. These divergences, supported by evidence of distinct entities through delimitation analyses, indicate potential cryptic diversity within these populations. In conclusion, this study represents the first molecular genetic analysis of bird chiggers in Malaysia, revealing varying levels of genetic divergence. Our findings highlight the utility of DNA barcoding for understanding chigger diversity and aiding in accurate identification.

DNA barcoding and metabarcoding are now widely used to advance species discovery and biodiversity assessments. High-throughput sequencing (HTS) has expanded the volume and scope of these analyses, but elevated error rates introduce noise into sequence records that can inflate estimates of biodiversity. Denoising -the separation of biological signal from instrument (technical) noise-of barcode and metabarcode data currently employs abundance-based methods which do not capitalize on the highly conserved structure of the cytochrome c oxidase subunit I (COI) region employed as the animal barcode. This manuscript introduces debar, an R package that utilizes a profile hidden Markov model to denoise indel errors in COI sequences introduced by instrument error. In silico studies demonstrated that debar recognized 95% of artificially introduced indels in COI sequences. When applied to real-world data, debar reduced indel errors in circular consensus sequences obtained with the Sequel platform by 75%, and those generated on the Ion Torrent S5 by 94%. The false correction rate was less than 0.1%, indicating that debar is receptive to the majority of true COI variation in the animal kingdom. In conclusion, the debar package improves DNA barcode and metabarcode workflows by aiding the generation of more accurate sequences aiding the characterization of species diversity.