Evaluating next‐generation sequencing (NGS) methods for routine monitoring of wild bees: Metabarcoding,mitogenomics or NGS barcoding

Implementing cost‐effective monitoring programs for wild bees remains challenging due to the high costs of sampling and specimen identification. To reduce costs, next‐generation sequencing (NGS)‐based methods have lately been suggested as alternatives to morphology‐based identifications. To provide a comprehensive presentation of the advantages and weaknesses of different NGS‐based identification methods, we assessed three of the most promising ones, namely metabarcoding, mitogenomics and NGS barcoding. Using a regular monitoring data set (723 specimens identified using morphology), we found that NGS barcoding performed best for both species presence/absence and abundance data, producing only few false positives (3.4%) and no false negatives. In contrast, the proportion of false positives and false negatives was higher using metabarcoding and mitogenomics. Although strong correlations were found between biomass and read numbers, abundance estimates significantly skewed the communities' composition in these two techniques. NGS barcoding recovered the same ecological patterns as morphology. Ecological conclusions based on metabarcoding and mitogenomics were similar to those based on morphology when using presence/absence data, but different when using abundance data. In terms of workload and cost, we show that metabarcoding and NGS barcoding can compete with morphology, but not mitogenomics which was consistently more expensive. Based on these results, we advocate that NGS barcoding is currently the seemliest NGS method for monitoring of wild bees. Furthermore, this method has the advantage of potentially linking DNA sequences with preserved voucher specimens, which enable morphological re‐examination and will thus produce verifiable records which can be fed into faunistic databases.     

Method for quick DNA barcode reference library construction

DNA barcoding has become one of the most important techniques in plant species identification. Successful application of this technology is dependent on the availability of reference database of high species coverage. Unfortunately, there are experimental and data processing challenges to construct such a library within a short time. Here, we present our solutions to these challenges. We sequenced six conventional DNA barcode fragments (ITS1, ITS2, matK1, matK2, rbcL1, and rbcL2) of 380 flowering plants on next‐generation sequencing (NGS) platforms (Illumina Hiseq 2500 and Ion Torrent S5) and the Sanger sequencing platform. After comparing the sequencing depths, read lengths, base qualities, and base accuracies, we conclude that Illumina Hiseq2500 PE250 run is suitable for conventional DNA barcoding. We developed a new “Cotu” method to create consensus sequences from NGS reads for longer output sequences and more reliable bases than the other three methods. Step‐by‐step instructions to our method are provided. By using high‐throughput machines (PCR and NGS), labeling PCR, and the Cotu method, it is possible to significantly reduce the cost and labor investments for DNA barcoding. A regional or even global DNA barcoding reference library with high species coverage is likely to be constructed in a few years.     

DNA barcoding should accompany taxonomy - the case of Cerebratulus spp (Nemertea)

Many issues in DNA barcoding need to be solved before it can reach its goal to become a general database for species identification. While species delimitations are more or less well established in several taxa, there are still many groups where this is not the case. Without the proper taxonomic background/knowledge and corroboration with other kinds of data, the DNA barcoding approach may fail to identify species accurately. The classification and taxonomy of phylum Nemertea (nemerteans, ribbon worms) are traditionally based on morphology, but are not corroborated by an increasing amount of genetic data when it comes to classification either into species or into higher taxa. The taxonomy of the phylum needs to be improved before the full potential of DNA barcoding can be utilized to make sure that valid Linnean names accompany the barcode sequences. We illustrate the problematic situation in the phylum Nemertea by a case study from the genus Cerebratulus.     

Environmental barcoding: a next-generation sequencing approach for biomonitoring applications using river benthos

Timely and accurate biodiversity analysis poses an ongoing challenge for the success of biomonitoring programs. Morphology-based identification of bioindicator taxa is time consuming, and rarely supports species-level resolution especially for immature life stages. Much work has been done in the past decade to develop alternative approaches for biodiversity analysis using DNA sequence-based approaches such as molecular phylogenetics and DNA barcoding. On-going assembly of DNA barcode reference libraries will provide the basis for a DNA-based identification system. The use of recently introduced next-generation sequencing (NGS) approaches in biodiversity science has the potential to further extend the application of DNA information for routine biomonitoring applications to an unprecedented scale. Here we demonstrate the feasibility of using 454 massively parallel pyrosequencing for species-level analysis of freshwater benthic macroinvertebrate taxa commonly used for biomonitoring. We designed our experiments in order to directly compare morphology-based, Sanger sequencing DNA barcoding, and next-generation environmental barcoding approaches. Our results show the ability of 454 pyrosequencing of mini-barcodes to accurately identify all species with more than 1% abundance in the pooled mixture. Although the approach failed to identify 6 rare species in the mixture, the presence of sequences from 9 species that were not represented by individuals in the mixture provides evidence that DNA based analysis may yet provide a valuable approach in finding rare species in bulk environmental samples. We further demonstrate the application of the environmental barcoding approach by comparing benthic macroinvertebrates from an urban region to those obtained from a conservation area. Although considerable effort will be required to robustly optimize NGS tools to identify species from bulk environmental samples, our results indicate the potential of an environmental barcoding approach for biomonitoring programs.     

Assessing the performance of DNA barcoding using posterior predictive simulations

Accurate estimates of biodiversity are required for research in a broad array of biological subdisciplines including ecology, evolution, systematics, conservation and biodiversity science. The use of statistical models and genetic data, particularly DNA barcoding, has been suggested as an important tool for remedying the large gaps in our current understanding of biodiversity. However, the reliability of biodiversity estimates obtained using these approaches depends on how well the statistical models that are used describe the evolutionary process underlying the genetic data. In this study, we utilize data from the Barcode of Life Database and posterior predictive simulations to assess the performance of DNA barcoding under commonly used substitution models. We demonstrate that the success of DNA barcoding varies widely across DNA substitution models and that model choice has a substantial impact on the number of operational taxonomic units identified (changing results by ~4–31%). Additionally, we demonstrate that the widely followed practice of a priori assuming the Kimura 2‐parameter model for DNA barcoding is statistically unjustified and should be avoided. Using both data‐based and inference‐based test statistics, we detect variation in model performance across taxonomic groups, clustering algorithms, genetic divergence thresholds and substitution models. Taken together, these results illustrate the importance of considering both model selection and model adequacy in studies quantifying biodiversity.     

Detecting invertebrate species in archived collections using next‐generation sequencing

Invertebrate biodiversity measured at mostly family level is widely used in biological monitoring programmes to assess anthropogenic impacts on ecosystems. However, next‐generation sequencing (NGS) could allow development of new more sensitive biomonitoring tools by allowing rapid species identification. This could be accelerated if archived invertebrate collections and environmental information from past programmes are used to understand species distributions and their environmental responses. In this study, we take archived macroinvertebrate samples from two sites collected on multiple occasions and test whether NGS can successfully detect species. Samples had been stored in 70% ethanol at room temperature for up to 12 years. Three amplicons ranging from 197 to 274 bps within the DNA barcode region were amplified from samples and compared to DNA barcoding libraries to identify species. We were able to amplify partial DNA barcodes from most samples, and species were often detected with multiple amplicons. However, some singletons and taxa poorly covered by DNA barcoding were missed. This suggests additional DNA barcodes will be required to fill ‘gaps’ in current DNA barcode libraries for aquatic macroinvertebrates and/or that it may not be possible to detect all taxa in a sample. Furthermore, older samples often detected fewer taxa and were less reliable for amplification, suggesting NGS is best used on samples within 8 years of collection. Nevertheless, many common taxa with existing DNA barcodes were reliably identified with NGS and were often present at sites across multiple years, showing the potential of NGS for detecting common and abundant species in archived material.     

|SE|S|AM|E| Barcode: NGS‐oriented software for amplicon characterization – application to species and environmental barcoding

Progress in NGS technologies has opened up new opportunities for characterizing biodiversity, both for individual specimen identification and for environmental barcoding. Although the amount of data available to biologist is increasing, user‐friendly tools to facilitate data analysis have yet to be developed. Our aim, with |SE|S|AM|E| Barcode, is to provide such support through a unified platform. The sequences are analysed through a pipeline that (i) processes NGS amplicon runs, filtering markers and samples, (ii) builds reference libraries and finally (iii) identifies (barcodes) the sequences in each amplicon from the reference library. We use a simulated data set for specimen identification and a recently published data set for environmental barcoding to validate the method. The results obtained are consistent with the expected characterizations (in silico and previously published, respectively). |SE|S|AM|E| Barcode and its documentation are freely available under the Creative Commons Attribution‐NonCommercial‐ShareAlike 3.0 Unported Licence for Windows and Linux from http://www1.montpellier.inra.fr/CBGP/NGS/ .     

On Estimation of Allele Frequencies via Next-Generation DNA Resequencing with Barcoding

Next Generation Sequencing (NGS) has revolutionized biomedical research in recent years. It is now commonly used to identify rare variants through resequencing individual genomes. Due to the cost of NGS, researchers have considered pooling samples as a cost-effective alternative to individual sequencing. In this article, we consider the estimation of allele frequencies of rare variants through the NGS technologies with pooled DNA samples with or without barcodes. We consider three methods for estimating allele frequencies from such data, including raw sequencing counts, inferred genotypes, and expected minor allele counts, and compare their performance. Our simulation results suggest that the estimator based on inferred genotypes overall performs better than or as well as the other two estimators. When the sequencing coverage is low, biases and MSEs can be sensitive to the choice of the prior probabilities of genotypes for the estimators based on inferred genotypes and expected minor allele counts so that more accurate specification of prior probabilities is critical to lower biases and MSEs. Our study shows that the optimal number of barcodes in a pool is relatively robust to the frequencies of rare variants at a specific coverage depth. We provide general guidelines on using DNA pooling with barcoding for the estimation of allele frequencies of rare variants.     

Coalescing molecular evolution and DNA barcoding

The DNA barcoding concept (Woese et al. 1990 ; Hebert et al. 2003 ) has considerably boosted taxonomy research by facilitating the identification of specimens and discovery of new species. Used alone or in combination with DNA metabarcoding on environmental samples (Taberlet et al. 2012 ), the approach is becoming a standard for basic and applied research in ecology, evolution and conservation across taxa, communities and ecosystems (Scheffers et al. 2012 ; Kress et al. 2015 ). However, DNA barcoding suffers from several shortcomings that still remain overlooked, especially when it comes to species delineation (Collins & Cruickshank 2012 ). In this issue of Molecular Ecology, Barley & Thomson ( 2016 ) demonstrate that the choice of models of sequence evolution has substantial impacts on inferred genetic distances, with a propensity of the widely used Kimura 2‐parameter model to lead to underestimated species richness. While DNA barcoding has been and will continue to be a powerful tool for specimen identification and preliminary taxonomic sorting, this work calls for a systematic assessment of substitution models fit on barcoding data used for species delineation and reopens the debate on the limitation of this approach.     

DNA条形码分析方法研究进展

DNA条形码是一段短的、标准化的DNA序列,DNA条形码技术通过对DNA条形码序列分析实现物种的有效鉴定.随着生物DNA条形码序列的大量测定,DNA条形码分析方法得到迅速发展,推动了其在生物分子鉴定中的应用.2003年以来,DNA条形码技术已广泛应用于动物、植物和真菌等物种的鉴定,并有力地推动了生物分类学、生物多样性和生态学等学科的发展.本文在综述DNA条形码技术的基础上,总结了5类主要的DNA条形码分析方法,即基于遗传距离的分析、基于遗传相似度的分析、基于系统发育树的分析、基于序列特征的分析和基于统计分类法的分析,并进一步展望了DNA条形码技术的发展与应用.     

Is DNA Barcoding Actually Cheaper and Faster than Traditional Morphological Methods: Results from a Survey of Freshwater Bioassessment Efforts in the United States?

Taxonomic identification accounts for a substantial portion of cost associated with bioassessment programs across the United States. New analytical approaches, such as DNA barcoding have been promoted as a way to reduce monitoring costs and improve efficiency, yet this assumption has not been thoroughly evaluated. We address this question by comparing costs for traditional morphology-based bioassessment, the standard Sanger sequencing-based DNA barcoding approach, and emerging next-generation (NGS) molecular methods. Market demand for molecular approaches is also assessed through a survey of the level of freshwater bioassessment effort in the United States across multiple habitat types (lakes, streams, wetlands) and indicators (benthic invertebrates, fish, algae). All state and regional level programs administered by public agencies and reported via agency web sites were included in the survey. Costs were based on surveys of labs and programs willing to provide such information. More than 19,500 sites are sampled annually across the United States, with the majority of effort occurring in streams. Benthic invertebrates are the most commonly used indicator, but algae and fish comprise between 35% and 21% of total sampling effort, respectively. We estimate that between $104 and $193 million is spent annually on routine freshwater bioassessment in the United States. Approximately 30% of the bioassessment costs are comprised of the cost to conduct traditional morphology-based taxonomy. Current barcoding costs using Sanger sequencing are between 1.7 and 3.4 times as expensive as traditional taxonomic approaches, excluding the cost of field sampling (which is common to both approaches). However, the cost of NGS methods are comparable (or slightly less expensive) than traditional methods depending on the indicator. The promise of barcoding as a cheaper alternative to current practices is not yet realized, although molecular methods may provide other benefits, such as a faster sample processing and increased taxonomic resolution.     

Pay Attention to the Overlooked Cryptic Diversity in Existing Barcoding Data: the Case of Mollusca with Character-Based DNA Barcoding

With the global biodiversity crisis, DNA barcoding aims for fast species identification and cryptic species diversity revelation. For more than 10 years, large amounts of DNA barcode data have been accumulating in publicly available databases, most of which were conducted by distance or tree-building methods that have often been argued, especially for cryptic species revelation. In this context, overlooked cryptic diversity may exist in the available barcoding data. The character-based DNA barcoding, however, has a good chance for detecting the overlooked cryptic diversity. In this study, marine mollusk was as the ideal case for detecting the overlooked potential cryptic species from existing cytochrome c oxidase I (COI) sequences with character-based DNA barcode. A total of 1081 COI sequences of mollusks, belonging to 176 species of 25 families of Gastropoda, Cephalopoda, and Lamellibranchia, were conducted by character analysis. As a whole, the character-based barcoding results were consistent with previous distance and tree-building analysis for species discrimination. More importantly, quite a number of species analyzed were divided into distinct clades with unique diagnostical characters. Based on the concept of cryptic species revelation of character-based barcoding, these species divided into separate taxonomic groups might be potential cryptic species. The detection of the overlooked potential cryptic diversity proves that the character-based barcoding mode possesses more advantages of revealing cryptic biodiversity. With the development of DNA barcoding, making the best use of barcoding data is worthy of our attention for species conservation.     

COI-based DNA barcoding of Arcoida species (Bivalvia: Pteriomorphia) along the coast of China

DNA barcoding is a promising tool for the rapid and unambiguous identification of species. Some arcoid species are particularly difficult to distinguish with traditional morphological identification owing to phenotypic variation and the existence of closely related taxa. Here, we apply DNA barcoding based on mitochondrial cytochrome c oxidase I gene (COI) to arcoid species collected from the coast along China. Combining morphology with molecular data indicates the 133 specimens of Arcoida could be assigned to 24 species. Because of the deep genetic divergence within Tegillarca granosa, there was an overlap between genetic variation within species and variation between species. Nevertheless, NJ and Bayesian trees showed that all species fell into reciprocally monophyletic clades with high bootstrap values. Our results evidence that the COI marker can efficiently identify species, correct mistakes caused by morphological identification and reveal genetic differentiation among populations within species. This study provides a clear example of the usefulness of barcoding for arcoid identification. Furthermore, it also lays a foundation for other biological and ecological studies of Arcoida.     

DNA barcoding,microarrays and next generation sequencing: recent tools for genetic diversity estimation and authentication of medicinal plants

DNA barcoding, microarray technology and next generation sequencing have emerged as promising tools for the elucidation of plant genetic diversity and its conservation. They are proving to be immensely helpful in authenticating the useful medicinal plants for herbal drug preparations. These newer versions of molecular markers utilize short genetic markers in the genome to characterize the organism to a particular species. This has the potential not only to classify the known and yet unknown species but also has a promising future to link the medicinally important plants according to their properties. The newer trends being followed in DNA chips and barcoding pave the way for a future with many different possibilities. Several of these possibilities might be: characterization of unknown species in a considerably less time than usual, identification of newer medicinal properties possessed by the species and also updating the data of the already existing but unnoticed properties. This can assist us to cure many different diseases and will also generate novel opportunities in medicinal drug delivery and targeting.     

When to use next generation sequencing or diagnostic PCR in diet analyses

Next‐generation sequencing (NGS) is increasingly used for diet analyses; however, it may not always describe diet samples well. A reason for this is that diet samples contain mixtures of food DNA in different amounts as well as consumer DNA which can reduce the food DNA characterized. Because of this, detections will depend on the relative amount and identity of each type of DNA. For such samples, diagnostic PCR will most likely give more reliable results, as detection probability is only marginally dependent on other copresent DNA. We investigated the reliability of each method to test (a) whether predatory beetle regurgitates, supposed to be low in consumer DNA, allow to retrieve prey sequences using general barcoding primers that co‐amplify the consumer DNA, and (b) to assess the sequencing depth or replication needed for NGS and diagnostic PCR to give stable results. When consumer DNA is co‐amplified, NGS is better suited to discover the range of possible prey, than for comparing co‐occurrences of diet species between samples, as retested samples were repeatedly different in prey detections with this approach. This shows that samples were incompletely described, as prey detected by diagnostic PCR frequently were missed by NGS. As the sequencing depth needed to reliably describe the diet in such samples becomes very high, the cost‐efficiency and reliability of diagnostic PCR make diagnostic PCR better suited for testing large sample‐sets. Especially if the targeted prey taxa are thought to be of ecological importance, as diagnostic PCR gave more nested and consistent results in repeated testing of the same sample.     

DNA Barcoding is not enough: mismatch of taxonomy and genealogy in New Zealand grasshoppers (Orthoptera: Acrididae).

DNA barcoding has been touted as a program that will efficiently and relatively cheaply inform on biological diversity; yet many exemplars purporting to demonstrate the efficacy of the method have been undertaken by its principal proponents. Critics of DNA barcoding identify insufficient within-taxon sampling coupled with the knowledge that levels of haplotypic paraphyly are rather high as key reasons to be sceptical of the value of an exclusively DNA-based taxonomic. Here I applied a DNA barcoding approach using mtDNA sequences from the cytochrome oxidase I gene to examine diversity in a group of endemic New Zealand grasshoppers belonging to the genus Sigaus . The mtDNA data revealed high genetic distances among individuals of a single morpho-species, but this diversity was geographically partitioned. Phylogenetic analysis supported at least four haplogroups within one species ( Sigaus australis ) but paraphyly of this species with respect to several others. In some instances two morphologically and ecologically distinct species shared identical mtDNA haplotypes. The mismatch of genealogy and taxonomy revealed in the Sigaus australis complex indicates that, if used in isolation, DNA barcoding data can be highly misleading about biodiversity. Furthermore, failure to take into account evidence from natural history and morphology when utilizing DNA barcoding will tend to conceal the underlying evolutionary processes associated with speciation.
© The Willi Hennig Society 2007.     

Current progress in DNA barcoding and future implications for entomology

DNA barcoding is a technique for identifying organisms based on a short, standardized fragment of genomic DNA. The standardized sequence region is called a DNA barcode because it is like a barcode tag for each taxon. Since the proposition of this concept and the launch of a large project named the Barcode of Life, this simple technique has attracted attention from taxonomists, ecologists, conservation biologists, agriculturists, plant‐quarantine officers and others, and the number of studies using the DNA barcode has rapidly increased. The extreme diversity of insects and their economical, epidemiological and agricultural importance have made this group a major target of DNA barcoding. However, there is some controversy about the utility of DNA barcoding. In this review, we present an overview of DNA barcoding and its application to entomology. We also introduce current advances and future implications of this promising technique.     

Sorting specimen‐rich invertebrate samples with cost‐effective NGS barcodes: Validating a reverse workflow for specimen processing

Biologists frequently sort specimen‐rich samples to species. This process is daunting when based on morphology, and disadvantageous if performed using molecular methods that destroy vouchers (e.g., metabarcoding). An alternative is barcoding every specimen in a bulk sample and then presorting the specimens using DNA barcodes, thus mitigating downstream morphological work on presorted units. Such a “reverse workflow” is too expensive using Sanger sequencing, but we here demonstrate that is feasible with an next‐generation sequencing (NGS) barcoding pipeline that allows for cost‐effective high‐throughput generation of short specimen‐specific barcodes (313 bp of COI; laboratory cost <$0.50 per specimen) through next‐generation sequencing of tagged amplicons. We applied our approach to a large sample of tropical ants, obtaining barcodes for 3,290 of 4,032 specimens (82%). NGS barcodes and their corresponding specimens were then sorted into molecular operational taxonomic units (mOTUs) based on objective clustering and Automated Barcode Gap Discovery (ABGD). High diversity of 88–90 mOTUs (4% clustering) was found and morphologically validated based on preserved vouchers. The mOTUs were overwhelmingly in agreement with morphospecies (match ratio 0.95 at 4% clustering). Because of lack of coverage in existing barcode databases, only 18 could be accurately identified to named species, but our study yielded new barcodes for 48 species, including 28 that are potentially new to science. With its low cost and technical simplicity, the NGS barcoding pipeline can be implemented by a large range of laboratories. It accelerates invertebrate species discovery, facilitates downstream taxonomic work, helps with building comprehensive barcode databases and yields precise abundance information.     

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

All next-generation sequencing (NGS) procedures include assays performed at the laboratory bench ("wet bench") and data analyses conducted using bioinformatics pipelines ("dry bench"). Both elements are essential to produce accurate and reliable results, which are particularly critical for clinical laboratories. Targeted NGS technologies have increasingly found favor in oncology applications to help advance precision medicine objectives, yet the methods often involve disconnected and variable wet and dry bench workflows and uncoordinated reagent sets. In this report, we describe a method for sequencing challenging cancer specimens with a 21-gene panel as an example of a comprehensive targeted NGS system. The system integrates functional DNA quantification and qualification, single-tube multiplexed PCR enrichment, and library purification and normalization using analytically-verified, single-source reagents with a standalone bioinformatics suite. As a result, accurate variant calls from low-quality and low-quantity formalin-fixed, paraffin-embedded (FFPE) and fine-needle aspiration (FNA) tumor biopsies can be achieved. The method can routinely assess cancer-associated variants from an input of 400 amplifiable DNA copies, and is modular in design to accommodate new gene content. Two different types of analytically-defined controls provide quality assurance and help safeguard call accuracy with clinically-relevant samples. A flexible "tag" PCR step embeds platform-specific adaptors and index codes to allow sample barcoding and compatibility with common benchtop NGS instruments. Importantly, the protocol is streamlined and can produce 24 sequence-ready libraries in a single day. Finally, the approach links wet and dry bench processes by incorporating pre-analytical sample quality control results directly into the variant calling algorithms to improve mutation detection accuracy and differentiate false-negative and indeterminate calls. This targeted NGS method uses advances in both wetware and software to achieve high-depth, multiplexed sequencing and sensitive analysis of heterogeneous cancer samples for diagnostic applications.     

VIP Barcoding: composition vector‐based software for rapid species identification based on DNA barcoding

Species identification based on short sequences of DNA markers, that is, DNA barcoding, has emerged as an integral part of modern taxonomy. However, software for the analysis of large and multilocus barcoding data sets is scarce. The Basic Local Alignment Search Tool (BLAST) is currently the fastest tool capable of handling large databases (e.g. >5000 sequences), but its accuracy is a concern and has been criticized for its local optimization. However, current more accurate software requires sequence alignment or complex calculations, which are time‐consuming when dealing with large data sets during data preprocessing or during the search stage. Therefore, it is imperative to develop a practical program for both accurate and scalable species identification for DNA barcoding. In this context, we present VIP Barcoding: a user‐friendly software in graphical user interface for rapid DNA barcoding. It adopts a hybrid, two‐stage algorithm. First, an alignment‐free composition vector (CV) method is utilized to reduce searching space by screening a reference database. The alignment‐based K2P distance nearest‐neighbour method is then employed to analyse the smaller data set generated in the first stage. In comparison with other software, we demonstrate that VIP Barcoding has (i) higher accuracy than Blastn and several alignment‐free methods and (ii) higher scalability than alignment‐based distance methods and character‐based methods. These results suggest that this platform is able to deal with both large‐scale and multilocus barcoding data with accuracy and can contribute to DNA barcoding for modern taxonomy. VIP Barcoding is free and available at http://msl.sls.cuhk.edu.hk/vipbarcoding/ .