A from‐benchtop‐to‐desktop workflow for validating HTS data and for taxonomic identification in diet metabarcoding studies

The main objective of this work was to develop and validate a robust and reliable “from‐benchtop‐to‐desktop” metabarcoding workflow to investigate the diet of invertebrate‐eaters. We applied our workflow to faecal DNA samples of an invertebrate‐eating fish species. A fragment of the cytochrome c oxidase I (COI) gene was amplified by combining two minibarcoding primer sets to maximize the taxonomic coverage. Amplicons were sequenced by an Illumina MiSeq platform. We developed a filtering approach based on a series of nonarbitrary thresholds established from control samples and from molecular replicates to address the elimination of cross‐contamination, PCR/sequencing errors and mistagging artefacts. This resulted in a conservative and informative metabarcoding data set. We developed a taxonomic assignment procedure that combines different approaches and that allowed the identification of ~75% of invertebrate COI variants to the species level. Moreover, based on the diversity of the variants, we introduced a semiquantitative statistic in our diet study, the minimum number of individuals, which is based on the number of distinct variants in each sample. The metabarcoding approach described in this article may guide future diet studies that aim to produce robust data sets associated with a fine and accurate identification of prey items.     

In silico and empirical evaluation of twelve metabarcoding primer sets for insectivorous diet analyses

During the most recent decade, environmental DNA metabarcoding approaches have been both developed and improved to minimize the biological and technical biases in these protocols. However, challenges remain, notably those relating to primer design. In the current study, we comprehensively assessed the performance of ten COI and two 16S primer pairs for eDNA metabarcoding, including novel and previously published primers. We used a combined approach of in silico, in vivo‐mock community (33 arthropod taxa from 16 orders), and guano‐based analyses to identify primer sets that would maximize arthropod detection and taxonomic identification, successfully identify the predator (bat) species, and minimize the time and financial costs of the experiment. We focused on two insectivorous bat species that live together in mixed colonies: the greater horseshoe bat (Rhinolophus ferrumequinum) and Geoffroy's bat (Myotis emarginatus). We found that primer degeneracy is the main factor that influences arthropod detection in silico and mock community analyses, while amplicon length is critical for the detection of arthropods from degraded DNA samples. Our guano‐based results highlight the importance of detecting and identifying both predator and prey, as guano samples can be contaminated by other insectivorous species. Moreover, we demonstrate that amplifying bat DNA does not reduce the primers' capacity to detect arthropods. We therefore recommend the simultaneous identification of predator and prey. Finally, our results suggest that up to one‐third of prey occurrences may be unreliable and are probably not of primary interest in diet studies, which may decrease the relevance of combining several primer sets instead of using a single efficient one. In conclusion, this study provides a pragmatic framework for eDNA primer selection with respect to scientific and methodological constraints.     

Comparing diversity levels in environmental samples: DNA sequence capture and metabarcoding approaches using 18S and COI genes

Environmental DNA studies targeting multiple taxa using metabarcoding provide remarkable insights into levels of species diversity in any habitat. The main drawbacks are the presence of primer bias and difficulty in identifying rare species. We tested a DNA sequence‐capture method in parallel with the metabarcoding approach to reveal possible advantages of one method over the other. Both approaches were performed using the same eDNA samples and the same 18S and COI regions, followed by high throughput sequencing. Metabarcoded eDNA libraries were PCR amplified with one primer pair from 18S and COI genes. DNA sequence‐capture libraries were enriched with 3,639 baits targeting the same gene regions. We tested amplicon sequence variants (ASVs) and operational taxonomic units (OTUs) in silico approaches for both markers and methods, using for this purpose the metabarcoding data set. ASVs methods uncovered more species for the COI gene, whereas the opposite occurred for the 18S gene, suggesting that clustering reads into OTUs could bias diversity richness especially using 18S with relaxed thresholds. Additionally, metabarcoding and DNA sequence‐capture recovered 80%–90% of the control sample species. DNA sequence‐capture was 8x more expensive, nonetheless it identified 1.5x more species for COI and 13x more genera for 18S than metabarcoding. Both approaches offer reliable results, sharing ca. 40% species and 72% families and retrieve more taxa when nuclear and mitochondrial markers are combined. eDNA metabarcoding is quite well established and low‐cost, whereas DNA‐sequence capture for biodiversity assessment is still in its infancy, is more time‐consuming but provides more taxonomic assignments.     

Metabarcoding for the parallel identification of several hundred predators and their prey: Application to bat species diet analysis

Assessing diet variability is of main importance to better understand the biology of bats and design conservation strategies. Although the advent of metabarcoding has facilitated such analyses, this approach does not come without challenges. Biases may occur throughout the whole experiment, from fieldwork to biostatistics, resulting in the detection of false negatives, false positives or low taxonomic resolution. We detail a rigorous metabarcoding approach based on a short COI minibarcode and two‐step PCR protocol enabling the “all at once” taxonomic identification of bats and their arthropod prey for several hundreds of samples. Our study includes faecal pellets collected in France from 357 bats representing 16 species, as well as insect mock communities that mimic bat meals of known composition, negative and positive controls. All samples were analysed using three replicates. We compare the efficiency of DNA extraction methods, and we evaluate the effectiveness of our protocol using identification success, taxonomic resolution, sensitivity and amplification biases. Our parallel identification strategy of predators and prey reduces the risk of mis‐assigning prey to wrong predators and decreases the number of molecular steps. Controls and replicates enable to filter the data and limit the risk of false positives, hence guaranteeing high confidence results for both prey occurrence and bat species identification. We validate 551 COI variants from arthropod including 18 orders, 117 family, 282 genus and 290 species. Our method therefore provides a rapid, resolutive and cost‐effective screening tool for addressing evolutionary ecological issues or developing “chirosurveillance” and conservation strategies.     

Effect of marker choice and thermal cycling protocol on zooplankton DNA metabarcoding studies

DNA metabarcoding is a promising approach for rapidly surveying biodiversity and is likely to become an important tool for measuring ecosystem responses to environmental change. Metabarcoding markers need sufficient taxonomic coverage to detect groups of interest, sufficient sequence divergence to resolve species, and will ideally indicate relative abundance of taxa present. We characterized zooplankton assemblages with three different metabarcoding markers (nuclear 18S rDNA, mitochondrial COI, and mitochondrial 16S rDNA) to compare their performance in terms of taxonomic coverage, taxonomic resolution, and correspondence between morphology‐ and DNA‐based identification. COI amplicons sequenced on separate runs showed that operational taxonomic units representing >0.1% of reads per sample were highly reproducible, although slightly more taxa were detected using a lower annealing temperature. Mitochondrial COI and nuclear 18S showed similar taxonomic coverage across zooplankton phyla. However, mitochondrial COI resolved up to threefold more taxa to species compared to 18S. All markers revealed similar patterns of beta‐diversity, although different taxa were identified as the greatest contributors to these patterns for 18S. For calanoid copepod families, all markers displayed a positive relationship between biomass and sequence reads, although the relationship was typically strongest for 18S. The use of COI for metabarcoding has been questioned due to lack of conserved primer‐binding sites. However, our results show the taxonomic coverage and resolution provided by degenerate COI primers, combined with a comparatively well‐developed reference sequence database, make them valuable metabarcoding markers for biodiversity assessment.     

Environmental metabarcodes for insects: in silico PCR reveals potential for taxonomic bias

Studies of insect assemblages are suited to the simultaneous DNA‐based identification of multiple taxa known as metabarcoding. To obtain accurate estimates of diversity, metabarcoding markers ideally possess appropriate taxonomic coverage to avoid PCR‐amplification bias, as well as sufficient sequence divergence to resolve species. We used in silico PCR to compare the taxonomic coverage and resolution of newly designed insect metabarcodes (targeting 16S) with that of existing markers [16S and cytochrome oxidase c subunit I (COI)] and then compared their efficiency in vitro. Existing metabarcoding primers amplified in silico <75% of insect species with complete mitochondrial genomes available, whereas new primers targeting 16S provided >90% coverage. Furthermore, metabarcodes targeting COI appeared to introduce taxonomic PCR‐amplification bias, typically amplifying a greater percentage of Lepidoptera and Diptera species, while failing to amplify certain orders in silico. To test whether bias predicted in silico was observed in vitro, we created an artificial DNA blend containing equal amounts of DNA from 14 species, representing 11 insect orders and one arachnid. We PCR‐amplified the blend using five primer sets, targeting either COI or 16S, with high‐throughput amplicon sequencing yielding more than 6 million reads. In vitro results typically corresponded to in silico PCR predictions, with newly designed 16S primers detecting 11 insect taxa present, thus providing equivalent or better taxonomic coverage than COI metabarcodes. Our results demonstrate that in silico PCR is a useful tool for predicting taxonomic bias in mixed template PCR and that researchers should be wary of potential bias when selecting metabarcoding markers.     

Exploring the accuracy of amplicon‐based internal transcribed spacer markers for a fungal community

With the continual improvement in high‐throughput sequencing technology and constant updates to fungal reference databases, the use of amplicon‐based DNA markers as a tool to reveal fungal diversity and composition in various ecosystems has become feasible. However, both primer selection and the experimental procedure require meticulous verification. Here, we computationally and experimentally evaluated the accuracy and specificity of three widely used or newly designed internal transcribed spacer (ITS) primer sets (ITS1F/ITS2, gITS7/ITS4 and 5.8S‐Fun/ITS4‐Fun). In silico evaluation revealed that primer coverage varied at different taxonomic levels due to differences in degeneracy and the location of primer sets. Using even and staggered mock community standards, we identified different proportions of chimeric and mismatch reads generated by different primer sets, as well as great variation in species abundances, suggesting that primer selection would affect the results of amplicon‐based metabarcoding studies. Choosing proofreading and high‐fidelity polymerase (KAPA HiFi) could significantly reduce the percentage of chimeric and mismatch sequences, further reducing inflation of operational taxonomic units. Moreover, for two types of environmental fungal communities, plant endophytic and soil fungi, it was demonstrated that the three primer sets could not reach a consensus on fungal community composition or diversity, and that primer selection, not experimental treatment, determines observed soil fungal community diversity and composition. Future DNA marker surveys should pay greater attention to potential primer effects and improve the experimental scheme to increase credibility and accuracy.     

Toward an ecoregion scale evaluation of eDNA metabarcoding primers: A case study for the freshwater fish biodiversity of the Murray–Darling Basin (Australia)

High‐throughput sequencing of environmental DNA (i.e., eDNA metabarcoding) has become an increasingly popular method for monitoring aquatic biodiversity. At present, such analyses require target‐specific primers to amplify DNA barcodes from co‐occurring species, and this initial amplification can introduce biases. Understanding the performance of different primers is thus recommended prior to undertaking any metabarcoding initiative. While multiple software programs are available to evaluate metabarcoding primers, all programs have their own strengths and weaknesses. Therefore, a robust in silico workflow for the evaluation of metabarcoding primers will benefit from the use of multiple programs. Furthermore, geographic differences in species biodiversity are likely to influence the performance of metabarcoding primers and further complicate the evaluation process. Here, an in silico workflow is presented that can be used to evaluate the performance of metabarcoding primers on an ecoregion scale. This workflow was used to evaluate the performance of published and newly developed eDNA metabarcoding primers for the freshwater fish biodiversity of the Murray–Darling Basin (Australia). To validate the in silico workflow, a subset of the primers, including one newly designed primer pair, were used in metabarcoding analyses of an artificial DNA community and eDNA samples. The results show that the in silico workflow allows for a robust evaluation of metabarcoding primers and can reveal important trade‐offs that need to be considered when selecting the most suitable primer. Additionally, a new primer pair was described and validated that allows for more robust taxonomic assignments and is less influenced by primer biases compared to commonly used fish metabarcoding primers.     

New mitochondrial primers for metabarcoding of insects,designed and evaluated using in silico methods

Insect metabarcoding has been mainly based on PCR amplification of short fragments within the “barcoding region” of the gene cytochrome oxidase I (COI). However, because of the variability of this gene, it has been difficult to design good universal PCR primers. Most primers used today are associated with gaps in the taxonomic coverage or amplification biases that make the results less reliable and impede the detection of species that are present in the sample. We identify new primers for insect metabarcoding using computational approaches (ecoprimers and degeprime ) applied to the most comprehensive reference databases of mitochondrial genomes of Hexapoda assembled to date. New primers are evaluated in silico against previously published primers in terms of taxonomic coverage and resolution of the corresponding amplicons. For the latter criterion, we propose a new index, exclusive taxonomic resolution, which is a more biologically meaningful measure than the standard index used today. Our results show that the best markers are found in the ribosomal RNA genes (12S and 16S); they resolve about 90% of the genetically distinct species in the reference database. Some markers in protein‐coding genes provide similar performance but only at much higher levels of primer degeneracy. Combining two of the best individual markers improves the effective taxonomic resolution with up to 10%. The resolution is strongly dependent on insect taxon: COI primers detect 40% of Hymenoptera, while 12S primers detect 12% of Collembola. Our results indicate that amplicon‐based metabarcoding of insect samples can be improved by choosing other primers than those commonly used today.     

Metabarcoding for stomach‐content analyses of Pygmy devil ray (Mobula kuhlii cf. eregoodootenkee): Comparing tissue and ethanol preservative‐derived DNA

The application of high‐throughput sequencing to retrieve multi‐taxon DNA from different substrates such as water, soil, and stomach contents has enabled species identification without prior knowledge of taxon compositions. Here we used three minibarcodes designed to target mitochondrial COI in plankton, 16S in fish, and 16S in crustaceans, to compare ethanol‐ and tissue‐derived DNA extraction methodologies for metabarcoding. The stomach contents of pygmy devilrays (Mobula kuhlii cf. eregoodootenkee) were used to test whether ethanol‐derived DNA would provide a suitable substrate for metabarcoding. The DNA barcoding assays indicated that tissue‐derived operational taxonomic units (OTUs) were greater compared to those from extractions performed directly on the ethanol preservative. Tissue‐derived DNA extraction is therefore recommended for broader taxonomic coverage. Metabarcoding applications should consider including the following: (i) multiple barcodes, both taxon specific (e.g., 12S or 16S) and more universal (e.g., COI or 18S) to overcome bias and taxon misidentification and (ii) PCR inhibitor removal steps that will likely enhance amplification yields. However, where tissue is limited or no longer available, but the ethanol‐preservative medium is still available, metabarcoding directly from ethanol does recover the majority of common OTUs, suggesting the ethanol‐retrieval method could be applicable for dietary studies. Metabarcoding directly from preservative ethanol may also be useful where tissue samples are limited or highly valued; bulk samples are collected, such as for rapid species inventories; or mixed‐voucher sampling is conducted (e.g., for plankton, insects, and crustaceans).     

MOTU analysis of ichthyoplankton biodiversity in the upper Yangtze River,China

Identification of ichthyoplankton is difficult because fish during early life stages often lack stable morphological characteristics; such difficulty in species identification can be a major hindrance in conducting ichthyoplankton surveys for fish biodiversity investigations. Here, we evaluated the feasibility of a molecular operational taxonomic unit (MOTU) approach for ichthyoplankton investigations, and describe fish biodiversity in the Jinshajiang section of the upper Yangtze River, China. The MOTUs were established by grouping specimens diverging less than 1.00% Kimura two‐parameter (K2P) distance units from their nearest neighbor within the same MOTU, based on previous work on between‐species divergences of the mitochondrial cytochrome C oxidase subunit I (COI) gene. Taxonomic assignment of the MOTUs was performed by comparing the MOTU sequences with the COI sequences of taxonomic species. Sixty‐eight MOTUs were inferred from 818 COI sequences of ichthyoplankton in the Jinshajiang river section. Among those, one MOTU was composed of two identified taxonomic species, and each of the other MOTUs was linked to a single, identified taxonomic species. Only 26 MOTUs were successfully identified to taxonomic species due to the limited reference database. Our results demonstrate that the MOTU approach can be applied successfully for analyzing biodiversity and identifying species of freshwater ichthyoplankton. Compared with previous ichthyoplankton investigations the richness of ichthyoplankton was very high. High diversity of ichthyoplankton noted in our study suggests that the Jinshajiang section should be an important target for fish biodiversity conservation in the Yangtze River.     

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.     

Mitochondrial DNA (COI) analyses reveal that amphipod diversity is associated with environmental heterogeneity in deep‐sea habitats

The relationship between species diversity and environmental parameters is poorly understood for the mobile macrofauna of deep‐sea habitats due to under‐sampling and subsequent lack of accurate taxonomic information. To redress this, cytochrome oxidase c subunit I (COI) DNA sequences were used to estimate species diversity and to compare phoxocephalid amphipod assemblages among 20 stations encompassing a range of environmental conditions. Two regions, east (Chatham Rise) and west (Challenger Plateau) of New Zealand were sampled to depths of 200–1200 m with an epibenthic sled. Using a comparison among identified morphospecies, we found a clear gap in sequence divergences between 6% and 13% and used a 6% threshold to designate molecular operational taxonomic units (MOTUs), as a surrogate to putative species. DNA sequences (n = 297) revealed high total diversity (n = 49 MOTUs), as well as high beta diversity (28 MOTUs found at single location only). Novel phoxocephalid MOTUs were found at most stations, especially on Challenger Plateau and the flanks of Chatham Rise. Analyses of interstation assemblages revealed a major split between regions, indicating minimal overlap in taxon distributions. A cluster of highly similar stations was identified, broadly distributed over the crest of Chatham Rise, in association with elevated food availability, probably resulting from higher surface productivity and relatively shallow depth. Accordingly, multivariate analysis revealed a strong correlation between phoxocephalid assemblages and food supply. This study highlights the value of molecular approaches, in particular COI sequences, for quantifying and comparing diversity in under‐sampled and/or under‐studied taxa.     

ITS1 versus ITS2 as DNA metabarcodes for fungi

The nuclear ribosomal Internal Transcribed Spacer ITS region is widely used as a DNA metabarcoding marker to characterize the diversity and composition of fungal communities. In amplicon pyrosequencing studies of fungal diversity, one of the spacers ITS1 or ITS2 of the ITS region is normally used. In this methodological study we evaluate the usability of ITS1 vs. ITS2 as a DNA metabarcoding marker for fungi. We analyse three data sets: two comprising ITS1 and ITS2 sequences of known taxonomic affiliations and a third comprising ITS1 and ITS2 environmental amplicon pyrosequencing data. Clustering analyses of sequences with known taxonomy using the bioinformatics pipeline ClustEx revealed that a 97% similarity cut‐off represent a reasonable threshold for estimating the number of known species in the data sets for both ITS1 and ITS2. However, no single threshold value worked well for all fungi at the same time within the curated UNITE database, and we found that the Operational Taxonomic Unit (OTU) concept is not easily translated into the level of species because many species are distributed over several clusters. Clustering analyses of the 134 692 ITS1 and ITS2 pyrosequences using a 97% similarity cut‐off revealed a high similarity between the two data sets when it comes to taxonomic coverage. Although some groups are under‐ or unrepresented in the two data sets due to, e.g. primer mismatches, our results indicate that ITS1 and ITS2 to a large extent yield similar results when used as DNA metabarcodes for fungi.     

obitools: a unix‐inspired software package for DNA metabarcoding

DNA metabarcoding offers new perspectives in biodiversity research. This recently developed approach to ecosystem study relies heavily on the use of next‐generation sequencing (NGS) and thus calls upon the ability to deal with huge sequence data sets. The obitools package satisfies this requirement thanks to a set of programs specifically designed for analysing NGS data in a DNA metabarcoding context. Their capacity to filter and edit sequences while taking into account taxonomic annotation helps to set up tailor‐made analysis pipelines for a broad range of DNA metabarcoding applications, including biodiversity surveys or diet analyses. The obitools package is distributed as an open source software available on the following website: http://metabarcoding.org/obitools . A Galaxy wrapper is available on the GenOuest core facility toolshed: http://toolshed.genouest.org .     

Blind assessment of vertebrate taxonomic diversity across spatial scales by clustering environmental DNA metabarcoding sequences

Human activities impact all ecosystems on Earth, which urges scientists to better understand biodiversity changes across temporal and spatial scales. Environmental DNA (eDNA) metabarcoding is a promising non-invasive method to assess species composition in a wide range of ecosystems. Yet, this method requires the completeness of a reference database, i.e. a list of DNA sequences attached to each species of the regional pool, which is rarely met. As an alternative, molecular operational taxonomic units (MOTUs) can be extracted as clusters of sequences. However, the extent to which the diversity of MOTUs can predict the diversity of species across spatial scales is unknown. Here, we used 196 samples along the Rhone river (France) for which the reference database is complete to assess whether a blind eDNA approach can reliably predict the ground-truth number of species at different spatial scales. Using the 12S rDNA teleo primer, we curated and clustered 60 million sequences into MOTUs using a new assembled bioinformatic pipeline. We show that stringent quality filters were necessary to remove artefact noise, notably MOTUs present in a single PCR replicate, which represented 55% of MOTUs (103). Post-clustering cleaning also removed 19 additional erroneous MOTUs and only discarded one truly present species. We then show that the diversity of retained fish MOTUs accurately predicted the local (α, r = 0.98) and regional (γ) ground-truth species diversity (67 MOTUs versus 63 species), but also the species dissimilarity between samples (β-diversity, r = 0.98). This work paves the way towards extending the use of eDNA metabarcoding in community ecology and biogeography despite major gaps in genetic reference databases.     

Quantitative and qualitative assessment of pollen DNA metabarcoding using constructed species mixtures

Pollen DNA metabarcoding—marker‐based genetic identification of potentially mixed‐species pollen samples—has applications across a variety of fields. While basic species‐level pollen identification using standard DNA barcode markers is established, the extent to which metabarcoding (a) correctly assigns species identities to mixes (qualitative matching) and (b) generates sequence reads proportionally to their relative abundance in a sample (quantitative matching) is unclear, as these have not been assessed relative to known standards. We tested the quantitative and qualitative robustness of metabarcoding in constructed pollen mixtures varying in species richness (1–9 species), taxonomic relatedness (within genera to across class) and rarity (5%–100% of grains), using Illumina MiSeq with the markers rbcL and ITS2. Qualitatively, species composition determinations were largely correct, but false positives and negatives occurred. False negatives were typically driven by lack of a barcode gap or rarity in a sample. Species richness and taxonomic relatedness, however, did not strongly impact correct determinations. False positives were likely driven by contamination, chimeric sequences and/or misidentification by the bioinformatics pipeline. Quantitatively, the proportion of reads for each species was only weakly correlated with its relative abundance, in contrast to suggestions from some other studies. Quantitative mismatches are not correctable by consistent scaling factors, but instead are context‐dependent on the other species present in a sample. Together, our results show that metabarcoding is largely robust for determining pollen presence/absence but that sequence reads should not be used to infer relative abundance of pollen grains.     

Deep-Sea,Deep-Sequencing: Metabarcoding Extracellular DNA from Sediments of Marine Canyons

Marine sediments are home to one of the richest species pools on Earth, but logistics and a dearth of taxonomic work-force hinders the knowledge of their biodiversity. We characterized α- and β-diversity of deep-sea assemblages from submarine canyons in the western Mediterranean using an environmental DNA metabarcoding. We used a new primer set targeting a short eukaryotic 18S sequence (ca. 110 bp). We applied a protocol designed to obtain extractions enriched in extracellular DNA from replicated sediment corers. With this strategy we captured information from DNA (local or deposited from the water column) that persists adsorbed to inorganic particles and buffered short-term spatial and temporal heterogeneity. We analysed replicated samples from 20 localities including 2 deep-sea canyons, 1 shallower canal, and two open slopes (depth range 100–2,250 m). We identified 1,629 MOTUs, among which the dominant groups were Metazoa (with representatives of 19 phyla), Alveolata, Stramenopiles, and Rhizaria. There was a marked small-scale heterogeneity as shown by differences in replicates within corers and within localities. The spatial variability between canyons was significant, as was the depth component in one of the canyons where it was tested. Likewise, the composition of the first layer (1 cm) of sediment was significantly different from deeper layers. We found that qualitative (presence-absence) and quantitative (relative number of reads) data showed consistent trends of differentiation between samples and geographic areas. The subset of exclusively benthic MOTUs showed similar patterns of β-diversity and community structure as the whole dataset. Separate analyses of the main metazoan phyla (in number of MOTUs) showed some differences in distribution attributable to different lifestyles. Our results highlight the differentiation that can be found even between geographically close assemblages, and sets the ground for future monitoring and conservation efforts on these bottoms of ecological and economic importance.     

Toward accurate species‐level metabarcoding of arthropod communities from the tropical forest canopy

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A comparison of droplet digital polymerase chain reaction (PCR), quantitative PCR and metabarcoding for species‐specific detection in environmental DNA

Targeted species‐specific and community‐wide molecular diagnostics tools are being used with increasing frequency to detect invasive or rare species. Few studies have compared the sensitivity and specificity of these approaches. In the present study environmental DNA from 90 filtered seawater and 120 biofouling samples was analyzed with quantitative PCR (qPCR), droplet digital PCR (ddPCR) and metabarcoding targeting the cytochrome c oxidase I (COI) and 18S rRNA genes for the Mediterranean fanworm Sabella spallanzanii. The qPCR analyses detected S. spallanzanii in 53% of water and 85% of biofouling samples. Using ddPCR S. spallanzanii was detected in 61% of water of water and 95% of biofouling samples. There were strong relationships between COI copy numbers determined via qPCR and ddPCR (water R² = 0.81, p < .001, biofouling R² = 0.68, p < .001); however, qPCR copy numbers were on average 125‐fold lower than those measured using ddPCR. Using metabarcoding there was higher detection in water samples when targeting the COI (40%) compared to 18S rRNA (5.4%). The difference was less pronounced in biofouling samples (25% COI, 29% 18S rRNA). Occupancy modelling showed that although the occupancy estimate was higher for biofouling samples (ψ = 1.0), higher probabilities of detection were derived for water samples. Detection probabilities of ddPCR (1.0) and qPCR (0.93) were nearly double metabarcoding (0.57 to 0.27 marker dependent). Studies that aim to detect specific invasive or rare species in environmental samples should consider using targeted approaches until a detailed understanding of how community and matrix complexity, and primer biases affect metabarcoding data.