Barcode Index Numbers Research Articles

Shedding light on some dark branches: The under‐appreciated diversity of gymnosome pteropods and their coiled thecosome prey in the Neotropics

AbstractHoloplanktonic organisms are thought to have enormous populations sizes, expansive geographic ranges, and low species diversity. Previous work suggests that pelagic gastropods are no exception to this generalization. However, most of these data are derived from temperate species, whereas the bulk of pteropod diversity occurs in the tropics. Here, we present DNA barcode data for COI focused on the under‐studied limacinoid, gymnosome, and pseudothecosome pteropods collected from the coastal waters of Panama. We applied four molecular species delimitation approaches to determine the number of operational taxonomic units (OTUs) identifiable from our sequences and all data available from Barcode of Life Database (BOLD) and GenBank and compared these to the Barcode Index Number generated by the BOLD. Assemble Species by Automatic Partitioning (ASAP), Poisson Tree Processes (PTP), Bayesian Poisson Tree Processes (bPTP), and Generalized Mixed Yule Coalescent (GMYC) methods generally gave congruent results and suggest that pteropod diversity in the tropics is significantly underrepresented both in DNA sequence databases and in the number of named OTUs. Of 42 specimens collected and sequenced, we recovered 16 OTUs, only one of which belonged to an OTU already represented in sequence databases. Neighbor‐joining trees including the previously published sequences show that in all three groups morphospecies can include genetically divergent lineages. Many very divergent (>15% from nearest neighbor) taxa are also still represented by only a single sequence, suggesting that there is a large amount of cryptic or pseudo‐cryptic diversity still to be described. To aid this future endeavor, we include some preliminary 16S data derived from new pteropod‐specific primers.

A DNA barcode reference library for the Tipulidae (Insecta, Diptera) of Germany.

Tipulidae, commonly known as true crane flies, represent one of the most species-rich dipteran families, boasting approximately 4,500 known species globally. Their larvae serve as vital decomposers across diverse ecosystems, prompting their frequent and close observation in biomonitoring programs. However, traditional morphological identification methods are laborious and time-consuming, underscoring the need for a comprehensive DNA barcode reference library to speed up species determination. In this study, we present the outcomes of the German Barcode of Life initiative focused on Tipulidae. Our DNA barcode library comprises 824 high-quality cytochrome c oxidase I (COI) barcodes encompassing 76 crane fly species, counting for ca. 54% of the German tipulid fauna. Our results significantly increased the number of European tipulid species available in the Barcode of Life Data System (BOLD) by 14%. Additionally, the number of barcodes from European tipulid specimens more than doubled, with an increase of 118%, bolstering the DNA resource for future identification inquiries. Employing diverse species delimitation algorithms - including the multi-rate Poisson tree processes model (mPTP), Barcode Index Number assignments (BIN), Assemble Species by Automatic Partitioning (ASAP), and the TaxCI R-script - we successfully match 76-86% of the morphologically identified species. Further validation through neighbor-joining tree topology analysis and comparison with 712 additional European tipulid barcodes yield a remarkable 89% success rate for the species identification of German tipulids based on COI barcodes. This comprehensive DNA barcode dataset not only enhances species identification accuracy but also serves as a pivotal resource for ecological and biomonitoring studies, fostering a deeper understanding of crane fly diversity and distribution across terrestrial landscapes.

An analysis of the gaps in the South African DNA barcoding library of ticks of veterinary and public health importance.

Ticks transmit pathogens of veterinary and public health importance. Understanding their diversity is critical as infestations lead to significant economic losses globally. To date, over 90 species across three families have been identified in South Africa. However, the taxonomy of most species has not been resolved due to morphological identification challenges. DNA barcoding through the Barcode of Life Data Systems (BOLD) is therefore a valuable tool for species verifications for biodiversity assessments. This study conducted an analysis of South African tick COI barcodes on BOLD by verifying species on checklists, literature, and other sequence databases. The compiled list represented 97 species, including indigenous (59), endemics (27), introduced (2), invasives (1), and eight that could not be classified. Analyses indicated that 31 species (32%) from 11 genera have verified COI barcodes. These are distributed across all nine provinces with the Eastern Cape having the highest species diversity, followed by Limpopo, with KwaZulu-Natal having the least diversity. Rhipicephalus, Hyalomma, and Argas species had multiple barcode index numbers, suggesting cryptic diversity or unresolved taxonomy. We identified 21 species of veterinary or zoonotic importance from the Argasidae and Ixodidae families that should be prioritised for barcoding. Coordinating studies and defining barcoding targets is necessary to ensure that tick checklists are updated to support decision-making for the control of vector-borne diseases and alien invasives.

Curating BOLD records via Bayesian phylogenetic assignments enables harmonization of regional subgeneric classifications and cryptic species detection within the genus Tachina (Diptera: Tachinidae)

Abstract DNA barcoding is a popular tool for species identification of insect samples, with important applications for plant protection. However, Barcode of Life Database queries related to tachinid samples can produce ambiguous results due to contradictory species assignments. Therefore, we applied Bayesian phylogenetic inference to 811 Tachina Meigen, 1803 COI-5P sequences containing all contradictory species assignments of Tachina Barcode Index Numbers. Based on phylogenetic assignment, the assemble species by automatic partitioning (ASAP) analysis, the MonoPhy test and analyses of genetic divergence, we identified 805 sequences representing species of the Tachina genus, whereas six sequences were incorrectly assigned to Tachina. The dataset contained 21 described species and at least seven unidentified species. Additionally, we found that the described species Tachina marklini Zetterstedt, 1838, includes two cryptic species based on ASAP partitioning of sequences, phylogenetic inference and geographical metadata. Furthermore, we harmonized conflicting subgeneric classifications of the Palearctic and Nearctic by employing different subgenera assignments from both partitions. We aimed at monophyletic subgenera partitions. We largely confirmed the validity of the Palearctic Tachina subgenera and Nowickia as a subgenus of Tachina. However, Palearctic Nowickia species formerly allocated to the outdated genus Fabriciella appeared to constitute one monophyletic group with the subgenus Rhachogaster. We conclude that this set of bioinformatics tools is suitable for curating COI-5P-based DNA barcode libraries. Although, curation is limited due to possible species introgression, horizontal gene transfer, incomplete lineage sorting and human errors the resulting dataset enabled the revision of subgenera concepts and the unambiguous cryptic species detection.

Delimiting species, revealing cryptic diversity in Molytinae (Coleoptera: Curculionidae) weevil through DNA barcoding.

The subfamily Molytinae (Coleoptera: Curculionidae), being the second largest group within the family Curculionidae, exhibits a diverse range of hosts and poses a serious threat to agricultural and forestry industries. We used 1,290 cytochrome c oxidase subunit I (COI) barcodes to assess the efficiency of COI barcodes in species differentiation and uncover cryptic species diversity within weevils of Molytinae. The average Kimura 2-parameter distances within species, genus, and subfamily were 2.90%, 11.0%, and 22.26%, respectively, indicating significant genetic differentiation at both levels. Moreover, there exists a considerable degree of overlap between intraspecific (0%-27.50%) and interspecific genetic distances (GDs; 0%-39.30%). The application of Automatic barcode gap discovery, Assemble Species by Automatic Partitioning, Barcode Index Number, Poisson Tree Processes (PTP), Bayesian Poisson Tree Processes (bPTP), and jMOTU resulted in the identification of 279, 275, 494, 322, 320, and 279 molecular operational taxonomic units, respectively. The integration of 6 methods successfully delimited species of Molytinae in 86.6% of all examined morphospecies, surpassing a threshold value of 3% GD (73.0%). A total of 28 morphospecies exhibiting significant intraspecific divergences were assigned to multiple MOTUs, respectively, suggesting the presence of cryptic diversity or population divergence. The identification of cryptic species within certain morphological species in this study necessitates further investigation through comprehensive taxonomic practices in the future.

Delimiting species, revealing cryptic diversity, and population divergence in Qinghai-Tibet Plateau weevils through DNA barcoding.

The Leptomias group represents one of the most diverse taxonomic group of weevils in the Qinghai-Tibet Plateau and its adjacent areas. Despite the potential of hidden diversity, relatively few comprehensive studies have been conducted on species diversity in this taxonomic group. In this study, we performed DNA barcoding analysis for species of the Leptomias group using a comprehensive DNA barcode dataset that included 476 sequences representing 54 morphospecies. Within the dataset, our laboratory contributed 474 sequences, and 390 sequences were newly generated for this study. The average Kimura 2-parameter distances among morphospecies and genera were 0.76% and 19.15%, respectively. In 94.4% of the species, the minimum interspecific distances exceeded the maximum intraspecific distances, indicating the presence of barcode gaps in most species of Leptomias group. The application of Automatic Barcode Gap Discovery, Assemble Species by Automatic Partitioning, Barcode Index Number, Bayesian Poisson tree processes, jMOTU, and Neighbor-joining tree methods revealed 45, 45, 63, 54, and 55 distinct clusters representing single species, respectively. Additionally, a total of four morphospecies, Leptomias kangmarensis, L. midlineatus, L. siahus, and L. sp.9RL, were found to be assigned to multiple subclade each, indicating the geographical divergences and the presence of cryptic diversity. Our findings of this study demonstrate that Qinghai-Tibet Plateau exhibits a higher species diversity of the Leptomias group, and it is imperative to investigate cryptic species within certain morphospecies using integrative taxonomic approaches in future studies. Moreover, the construction of a DNA barcode reference library presented herein establishes a robust foundational dataset to support forthcoming research on weevil taxonomy, phylogenetics, ecology, and evolution.

Unveiling South African insect diversity: DNA barcoding’s contribution to biodiversity data

Insects are one of the most species-rich groups on Earth. They comprise much of animal diversity and play vital roles in ecosystems, including pollination, pest control, and decomposition. However, only a fraction of this diversity has been formally described. South Africa is recognised as one of the most biologically diverse countries globally, with an estimated 44 000 insect species. Many crops rely on insect pollinators, including canola, apples, oranges, and sunflowers. A shortage of wild pollinators currently threatens crop yields, yet our knowledge of insect diversity within South Africa is sparse. There are few taxonomic specialists relative to South Africa’s biodiversity, and the methods used for insect identification can be time-consuming and expensive. DNA barcoding provides an important research tool to accelerate insect biodiversity research. In this review, we queried the public DNA barcoding BOLD (Barcode of Life Data System) database for records of “Insecta” within South Africa, and 416 211 published records assigned to 28 239 unique BINs (Barcode Index Numbers) were returned. We identified five taxonomic orders with more BINs than known species in southern Africa (Hymenoptera, Diptera, Thysanoptera, Plecoptera, and Strepsiptera). Most of the barcoded records were derived from Malaise trap sampling in Gauteng, Mpumalanga and Limpopo, while the rest of South Africa remains poorly sampled. We suggest that there is a need for a comprehensive national sampling effort alongside increased investment in taxonomic expertise to generate critical baseline data on insect biodiversity before species are lost to extinction.

The InBIO Barcoding Initiative Database: DNA barcodes of Portuguese moths.

The InBIO Barcoding Initiative (IBI) Dataset - DS-IBILP08 contains records of 2350 specimens of moths (Lepidoptera species that do not belong to the superfamily Papilionoidea). All specimens have been morphologically identified to species or subspecies level and represent 1158 species in total. The species of this dataset correspond to about 42% of mainland Portuguese Lepidoptera species. All specimens were collected in mainland Portugal between 2001 and 2022. All DNA extracts and over 96% of the specimens are deposited in the IBI collection at CIBIO, Research Center in Biodiversity and Genetic Resources. The authors enabled "The InBIO Barcoding Initiative Database: DNA barcodes of Portuguese moths" in order to release the majority of data of DNA barcodes of Portuguese moths within the InBIO Barcoding Initiative. This dataset increases the knowledge on the DNA barcodes of 1158 species from Portugal belonging to 51 families. There is an increase in DNA barcodes of 205% in Portuguese specimens publicly available. The dataset includes 61 new Barcode Index Numbers. All specimens have their DNA barcodes publicly accessible through BOLD online database and the distribution data can be accessed through the Global Biodiversity Information Facility (GBIF).

The InBIO Barcoding Initiative Database: DNA barcodes of Orthoptera from Portugal.

The InBIO Barcoding Initiative (IBI) Orthoptera dataset contains records of 420 specimens covering all the eleven Orthoptera families occurring in Portugal. Specimens were collected in continental Portugal from 2005 to 2021 and were morphologically identified to species level by taxonomists. A total of 119 species were identified corresponding to about 77% of all the orthopteran species known from continental Portugal. DNA barcodes of 54 taxa were made public for the first time at the Barcode of Life Data System (BOLD). Furthermore, the submitted sequences were found to cluster in 129 BINs (Barcode Index Numbers), 35 of which were new additions to the Barcode of Life Data System (BOLD). All specimens have their DNA barcodes publicly accessible through BOLD online database. Stenobothruslineatus is recorded for the first time for continental Portugal. This dataset greatly increases the knowledge on the DNA barcodes and distribution of Orthoptera from Portugal. All DNA extractions and most specimens are deposited in the IBI collection at CIBIO, Research Center in Biodiversity and Genetic Resources.

Species boundaries of the whiptail catfish Rineloricaria (Siluriformes: Loricariidae) from the Paraíba do Sul River drainage, southeastern Brazil, with species redescriptions and description of a new species.

Species of the catfish genus Rineloricaria are common in the Paraíba do Sul River basin, in southeastern Brazil; here we present a revision of the taxonomic diversity and geographic distribution of the species of the genus inhabiting the basin, based on novel morphologic and molecular data. Five species delimitation methods based on cytochrome C oxidase subunit 1 nucleotide sequences yielded comparable molecular operational taxonomic units. The automatic barcode gap discovery, assemble species by automatic partitioning, barcode index number, and Bayesian implementation of the Poisson tree process methods supported the recognition of five evolutionary lineages. These taxonomic units were assigned to the previously described Rineloricaria nigricauda, Rineloricaria steindachneri, Rineloricaria zawadzkii, and Rineloricaria nudipectoris, and an additional undescribed species. R. zawadzkii was further divided into two intraspecific geographically structured lineages using the generalized mixed Yule coalescent delimitation method. A maximum likelihood phylogenetic analysis revealed that the five lineages from the Paraíba do Sul have closer relationships to different species from southern and southeastern Brazil (Ribeira de Iguape, Lagoa dos Patos, Uruguay, Paraguay, and Parana river basins) than to each other. Based on the analysis of lectotypes, recently collected material, and specimens from ichthyological collections, the poorly described R. nigricauda and R. steindachneri are redescribed following current descriptive standards. The undescribed species from the middle and upper Paraíba do Sul River basin is formally described. The description of a new species, along with the description of species boundaries in R. nigricauda and R. steindachneri, contributes to the knowledge of the ichthyofauna of the Paraíba do Sul River basin and adjacent coastal drainages of southeastern Brazil. An identification key for the species of Rineloricaria occurring in the Paraíba do Sul River basin is provided.

A DNA barcode reference library of Croatian mosquitoes (Diptera: Culicidae): implications for identification and delimitation of species, with notes on the distribution of potential vector species

BackgroundMosquitoes pose a risk to human health worldwide, and correct species identification and detection of cryptic species are the most important keys for surveillance and control of mosquito vectors. In addition to traditional identification based on morphology, DNA barcoding has recently been widely used as a complementary tool for reliable identification of mosquito species. The main objective of this study was to create a reference DNA barcode library for the Croatian mosquito fauna, which should contribute to more accurate and faster identification of species, including cryptic species, and recognition of relevant vector species.MethodsSampling was carried out in three biogeographical regions of Croatia over six years (2017–2022). The mosquitoes were morphologically identified; molecular identification was based on the standard barcoding region of the mitochondrial COI gene and the nuclear ITS2 region, the latter to identify species within the Anopheles maculipennis complex. The BIN-RESL algorithm assigned the COI sequences to the corresponding BINs (Barcode Index Number clusters) in BOLD, i.e. to putative MOTUs (Molecular Operational Taxonomic Units). The bPTP and ASAP species delimitation methods were applied to the genus datasets in order to verify/confirm the assignment of specimens to specific MOTUs.ResultsA total of 405 mosquito specimens belonging to six genera and 30 morphospecies were collected and processed. Species delimitation methods assigned the samples to 31 (BIN-RESL), 30 (bPTP) and 28 (ASAP) MOTUs, with most delimited MOTUs matching the morphological identification. Some species of the genera Culex, Aedes and Anopheles were assigned to the same MOTUs, especially species that are difficult to distinguish morphologically and/or represent species complexes. In total, COI barcode sequences for 34 mosquito species and ITS2 sequences for three species of the genus Anopheles were added to the mosquito sequence database for Croatia, including one individual from the Intrudens Group, which represents a new record for the Croatian mosquito fauna.ConclusionWe present the results of the first comprehensive study combining morphological and molecular identification of most mosquito species present in Croatia, including several invasive and vector species. With the exception of some closely related species, this study confirmed that DNA barcoding based on COI provides a reliable basis for the identification of mosquito species in Croatia.Graphical

Global arthropod beta-diversity is spatially and temporally structured by latitude

Global biodiversity gradients are generally expected to reflect greater species replacement closer to the equator. However, empirical validation of global biodiversity gradients largely relies on vertebrates, plants, and other less diverse taxa. Here we assess the temporal and spatial dynamics of global arthropod biodiversity dynamics using a beta-diversity framework. Sampling includes 129 sampling sites whereby malaise traps are deployed to monitor temporal changes in arthropod communities. Overall, we encountered more than 150,000 unique barcode index numbers (BINs) (i.e. species proxies). We assess between site differences in community diversity using beta-diversity and the partitioned components of species replacement and richness difference. Global total beta-diversity (dissimilarity) increases with decreasing latitude, greater spatial distance and greater temporal distance. Species replacement and richness difference patterns vary across biogeographic regions. Our findings support long-standing, general expectations of global biodiversity patterns. However, we also show that the underlying processes driving patterns may be regionally linked.

Molecular identification of Hymenopteran insects collected by using Malaise traps from Hazarganji Chiltan National Park Quetta, Pakistan.

The order Hymenoptera holds great significance for humans, particularly in tropical and subtropical regions, due to its role as a pollinator of wild and cultivated flowering plants, parasites of destructive insects and honey producers. Despite this importance, limited attention has been given to the genetic diversity and molecular identification of Hymenopteran insects in most protected areas. This study provides insights into the first DNA barcode of Hymenopteran insects collected from Hazarganji Chiltan National Park (HCNP) and contributes to the global reference library of DNA barcodes. A total of 784 insect specimens were collected using Malaise traps, out of which 538 (68.62%) specimens were morphologically identified as Hymenopteran insects. The highest abundance of species of Hymenoptera (133/538, 24.72%) was observed during August and least in November (16/538, 2.97%). Genomic DNA extraction was performed individually from 90/538 (16.73%) morphologically identified specimens using the standard phenol-chloroform method, which were subjected separately to the PCR for their molecular confirmation via the amplification of cytochrome c oxidase subunit 1 (cox1) gene. The BLAST analyses of obtained sequences showed 91.64% to 100% identities with related sequences and clustered phylogenetically with their corresponding sequences that were reported from Australia, Bulgaria, Canada, Finland, Germany, India, Israel, and Pakistan. Additionally, total of 13 barcode index numbers (BINs) were assigned by Barcode of Life Data Systems (BOLD), out of which 12 were un-unique and one was unique (BOLD: AEU1239) which was assigned for Anthidium punctatum. This indicates the potential geographical variation of Hymenopteran population in HCNP. Further comprehensive studies are needed to molecularly confirm the existing insect species in HCNP and evaluate their impacts on the environment, both as beneficial (for example, pollination, honey producers and natural enemies) and detrimental (for example, venomous stings, crop damage, and pathogens transmission).

Identification of fish specimens of the Tocantins River, Brazil, using DNA barcoding.

The fish fauna of the Tocantins River possesses many endemic species; however, it is little studied in molecular terms and is quite threatened by the construction of several hydroelectric dams. Therefore, the objective of this study was to identify the ichthyofauna of the Tocantins River using DNA barcoding. For this, collections were carried out in five points of this river, which resulted in the capture of 725 individuals from which partial sequences of the cytochrome oxidase subunit I (COI) gene were obtained for genetic analysis. A total of 443 haplotypes were recovered with the mean intraspecific K2P genetic distance of 1.82%. Altogether, 138 species were identified based on morphological criteria, which was a quantity that was much lower than that indicated by the four molecular methods (assemble species by automatic partitioning [ASAP], barcode index number [BIN], generalized mixed Yule coalescent (GMYC), and Bayesian Poisson tree processes [bPTP]) through which 152-157 molecular entities were identified. In all, 41 unique BINs were obtained based on the data generated in the BOLDSystems platform. According to the result indicated by ASAP (species delimitation approach considered the most appropriate in the present study), there was an increase of 17 molecular entities (12.32%), when compared to the number of species identified through their morphological criteria, as it can show cryptic diversity, candidates for new species, and misidentifications. There were 21 incongruities indicated between the different identification approaches for species. Therefore, it is suggested that these taxonomic problems be cautiously evaluated by experts to solve such taxonomic issues.

New faunistic data on Diptera (Hexapoda, Insecta) from the Ziarat Juniperus forest ecosystem (Pakistan).

This study presents the first faunistic record and DNA barcoding for some Diptera species recorded from the Juniperus forest ecosystem of Balochistan, Pakistan. DNA barcoding was used to explore species diversity of Dipterans and collections carried out using a Malaise trap between December 2018 to December 2019. This process involved sequencing the 658 bp Cytochrome Oxidase I (COI) gene. Amongst the collected Diptera specimens, nine families were identified, representing 13 genera. These species include Atherigonasoccata (Rondani, 1871), Atherigonavaria (Schiner, 1868), Chironomusdorsalis (Meigen, 1818), Eupeodescorollae (Linnaeus, 1758), Eristalistenax (Linnaeus,1758), Goniaornata (Meigen, 1826), Luciliasericata (Meigen, 1826), Paragusquadrifasciatus (Linnaeus, 1758), Polleniarudis (Fabricius, 1794), Raviniapernix (Thompson, 1869), Sarcophagadux (Thompson, 1869), Trupaneaamoena (Schiner, 1868) and Wohlfahrtiabella (Linnaeus, 1758). The families Syrphidae and Sarcophagidae exhibited the highest representation, each comprising three genera and three species. They were followed by the family Muscidae, which had a single genus and two species. Anthomyiidae, Chironomidae, Calliphoridae, Polleniidae, Tachinidae and Tephritidae were represented by only one genus and one species. A nique Barcode Index Number (BIN) was allotted to Tachinidae (specie i.e Goniaornata). The results indicated that barcoding through cytochrome oxidase I is an effective approach for the accurate identification and genetic studies of Diptera species. This discovery highlights the significant diversity of this insect order in study region. Furthermore, a comprehensive list of other Diptera species remains elusive because of difficulties in distinguishing them, based on morphology and a lack of professional entomological knowledge.

Illuminating arthropod diversity in a tropical forest: Assessing biodiversity by automatic light trapping and DNA metabarcoding

AbstractAlthough studies of insect decline have recently dominated headlines worldwide, their interpretation requires caution since for most species, we lack long‐term population baselines. In the tropics, where most insect species thrive, our knowledge is even more limited and so reliable insect assessments must originate from well‐established long‐term monitoring efforts. Combining the extensive monitoring data from the Arthropod Program of the Smithsonian Tropical Research Institute (STRI) on Barro Colorado Island (BCI), Panama, we compare whether known arthropod diversity can be detected through metabarcoding of bulk insect samples obtained through automatic light‐trapping. Our study detected 4402 species based on Barcode Index Numbers (BIN) and detected fine‐scale differences between wet and dry seasons and sampling localities. We further refined our analysis to indicate which families and genera explained seasonal turnover. Using samples collected in parallel, but sorted manually as part of the ongoing arthropod monitoring program, we compared these methods. Out of 538 BINs recovered through manual sorting, there was a 70% overlap with the metabarcoding data; however, it represented 30% of the total BINs detected through metabarcoding. Expecting higher detection through metabarcoding, we also compare the results with the 14 years of sampling in BCI to better understand how well the monitoring program has captured the diversity of focal groups. Our results revealed a ~50% overlap between both methods and similar total catch. Barcode Index Numbers manually detected but not recovered by metabarcoding highlight some of the limitations of molecular detection methods such as primer bias. Contrastingly, BINs detected with metabarcoding, but not recovered by the traditional monitoring scheme, highlight the importance of local and regional barcode reference libraries.

DNA Barcoding of Central European Gasteruptiidae and the rarely-collected families Evaniidae, Stephanidae, Trigonalidae, and Aulacidae (Hymenoptera, Apocrita).

The study presents DNA barcoding results of five families of Hymenoptera in Germany. DNA barcodes are provided for 24 of the 25 species of Gasteruption occurring in Central Europe, including 18 of the 19 species recorded from Germany. The genetic diversity was higher than expected, with five species exhibiting two or more Barcode Index Number (BINs), whereas BIN sharing occurred in four species. Gasteruptionfoveiceps Semenov, 1892, stat. nov. is removed from synonymy with G.nigrescens Schletterer, 1885 and treated as a distinct species.

Assessing arthropod biodiversity with DNA barcoding in Jinnah Garden, Lahore, Pakistan.

Previous difficulties in arthropod taxonomy (such as limitations in conventional morphological approaches, the possibility of cryptic species and a shortage of knowledgeable taxonomists) has been overcome by the powerful tool of DNA barcoding. This study presents a thorough analysis of DNA barcoding in regards to Pakistani arthropods, which were collected from Lahore's Jinnah Garden. The 88 % (9,451) of the 10,792 specimens that were examined were able to generate DNA barcodes and 83% (8,974) of specimens were assigned 1,361 barcode index numbers (BINs). However, the success rate differed significantly between the orders of arthropods, from 77% for Thysanoptera to an astounding 93% for Diptera. Through morphological exams, DNA barcoding, and cross-referencing with the Barcode of Life Data system (BOLD), the Barcode Index Numbers (BINs) were assigned with a high degree of accuracy, both at the order (100%) and family (98%) levels. Though, identifications at the genus (37%) and species (15%) levels showed room for improvement. This underscores the ongoing need for enhancing and expanding the DNA barcode reference library. This study identified 324 genera and 191 species, underscoring the advantages of DNA barcoding over traditional morphological identification methods. Among the 17 arthropod orders identified, Coleoptera, Diptera, Hemiptera, Hymenoptera, and Lepidoptera from the class Insecta dominated, collectively constituting 94% of BINs. Expected malaise trap Arthropod fauna in Jinnah Garden could contain approximately 2,785 BINs according to Preston log-normal species distribution, yet the Chao-1 Index predicts 2,389.74 BINs. The Simpson Index of Diversity (1-D) is 0.989, signaling high species diversity, while the Shannon Index is 5.77, indicating significant species richness and evenness. These results demonstrated that in Pakistani arthropods, DNA barcoding and BOLD are an invaluable tool for improving taxonomic understanding and biodiversity assessment, opening the door for further eDNA and metabarcoding research.

DNA barcoding of the genus Gampsocleis (Orthoptera, Tettigoniidae) from China.

DNA barcoding is a useful addition to the traditional morphology-based taxonomy. A ca. 650 bp fragment of the 5' end of mitochondrial cytochrome c oxidase subunit I (hereafter COI-5P) DNA barcoding was sued as a practical tool for Gampsocleis species identification. DNA barcodes from 889 specimens belonging to 8 putative Gampsocleis species was analyzed, including 687 newly generated DNA barcodes. These barcode sequences were clustered/grouped into Operational Taxonomic Units (OTUs) using the criteria of five algorithms, namely Barcode Index Number (BIN) System, Assemble Species by Automatic Partitioning (ASAP), a Java program uses an explicit, determinate algorithm to define Molecular Operational Taxonomic Unit (jMOTU), Generalized Mixed Yule Coalescent (GMYC), and Bayesian implementation of the Poisson Tree Processes model (bPTP). The Taxon ID Tree grouped sequences of morphospecies and almost all MOTUs in distinct nonoverlapping clusters. Both long- and short-winged Gampsocleis species are reciprocally monophyletic in the Taxon ID Tree. In BOLD, 889 barcode sequences are assigned to 17 BINs. The algorithms ASAP, jMOTU, bPTP and GMYC clustered the barcode sequences into 6, 13, 10, and 23 MOTUs, respectively. BIN, ASAP, and bPTP algorithm placed three long-winged species, G. sedakovii, G. sinensis and G. ussuriensis within the same MOTU. All species delimitation algorithms split two short-winged species,G. fletcheri and G. gratiosa into at least two MOTUs each, except for ASAP algorithm. More detailed molecular and morphological integrative studies are required to clarify the status of these MOTUs in the future.

Delimiting Species with Single-Locus DNA Sequences.

DNA sequences are increasingly used for large-scale biodiversity inventories. Because these genetic data avoid the time-consuming initial sorting of specimens based on their phenotypic attributes, they have been recently incorporated into taxonomic workflows for overlooked and diverse taxa. Major statistical developments have accompanied this new practice, and several models have been proposed to delimit species with single-locus DNA sequences. However, proposed approaches to date make different assumptions regarding taxon lineage history, leading to strong discordance whenever comparisons are made among methods. Distance-based methods, such as Automatic Barcode Gap Discovery (ABGD) and Assemble Species by Automatic Partitioning (ASAP), rely on the detection of a barcode gap (i.e., the lack of overlap in the distributions of intraspecific and interspecific genetic distances) and the associated threshold in genetic distances. Network-based methods, as exemplified by the REfined Single Linkage (RESL) algorithm for the generation of Barcode Index Numbers (BINs), use connectivity statistics to hierarchically cluster-related haplotypes into molecular operational taxonomic units (MOTUs) which serve as species proxies. Tree-based methods, including Poisson Tree Processes (PTP) and the General Mixed Yule Coalescent (GMYC), fit statistical models to phylogenetic trees by maximum likelihood or Bayesian frameworks.Multiple webservers and stand-alone versions of these methods are now available, complicating decision-making regarding the most appropriate approach to use for a given taxon of interest. For instance, tree-based methods require an initial phylogenetic reconstruction, and multiple options are now available for this purpose such as RAxML and BEAST. Across all examined species delimitation methods, judicious parameter setting is paramount, as different model parameterizations can lead to differing conclusions. The objective of this chapter is to guide users step-by-step through all the procedures involved for each of these methods, while aggregating all necessary information required to conduct these analyses. The "Materials" section details how to prepare and format input files, including options to align sequences and conduct tree reconstruction with Maximum Likelihood and Bayesian inference. The Methods section presents the procedure and options available to conduct species delimitation analyses, including distance-, network-, and tree-based models. Finally, limits and future developments are discussed in the Notes section. Most importantly, species delimitation methods discussed herein are categorized based on five indicators: reliability, availability, scalability, understandability, and usability, all of which are fundamental properties needed for any approach to gain unanimous adoption within the DNA barcoding community moving forward.