Comparing whole‐genome shotgun sequencing and DNA metabarcoding approaches for species identification and quantification of pollen species mixtures

Molecular identification of mixed‐species pollen samples has a range of applications in various fields of research. To date, such molecular identification has primarily been carried out via amplicon sequencing, but whole‐genome shotgun (WGS) sequencing of pollen DNA has potential advantages, including (1) more genetic information per sample and (2) the potential for better quantitative matching. In this study, we tested the performance of WGS sequencing methodology and publicly available reference sequences in identifying species and quantifying their relative abundance in pollen mock communities. Using mock communities previously analyzed with DNA metabarcoding, we sequenced approximately 200Mbp for each sample using Illumina HiSeq and MiSeq. Taxonomic identifications were based on the Kraken k‐mer identification method with reference libraries constructed from full‐genome and short read archive data from the NCBI database. We found WGS to be a reliable method for taxonomic identification of pollen with near 100% identification of species in mixtures but generating higher rates of false positives (reads not identified to the correct taxon at the required taxonomic level) relative to rbcL and ITS2 amplicon sequencing. For quantification of relative species abundance, WGS data provided a stronger correlation between pollen grain proportion and sequence read proportion, but diverged more from a 1:1 relationship, likely due to the higher rate of false positives. Currently, a limitation of WGS‐based pollen identification is the lack of representation of plant diversity in publicly available genome databases. As databases improve and costs drop, we expect that eventually genomics methods will become the methods of choice for species identification and quantification of mixed‐species pollen samples.     

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.     

Minimizing polymerase biases in metabarcoding

DNA metabarcoding is an increasingly popular method to characterize and quantify biodiversity in environmental samples. Metabarcoding approaches simultaneously amplify a short, variable genomic region, or “barcode,” from a broad taxonomic group via the polymerase chain reaction (PCR), using universal primers that anneal to flanking conserved regions. Results of these experiments are reported as occurrence data, which provide a list of taxa amplified from the sample, or relative abundance data, which measure the relative contribution of each taxon to the overall composition of amplified product. The accuracy of both occurrence and relative abundance estimates can be affected by a variety of biological and technical biases. For example, taxa with larger biomass may be better represented in environmental samples than those with smaller biomass. Here, we explore how polymerase choice, a potential source of technical bias, might influence results in metabarcoding experiments. We compared potential biases of six commercially available polymerases using a combination of mixtures of amplifiable synthetic sequences and real sedimentary DNA extracts. We find that polymerase choice can affect both occurrence and relative abundance estimates and that the main source of this bias appears to be polymerase preference for sequences with specific GC contents. We further recommend an experimental approach for metabarcoding based on results of our synthetic experiments.     

Endolichenic Fungal Community Analysis by Pure Culture Isolation and Metabarcoding: A Case Study of Parmotrema tinctorum

Lichen is a symbiotic mutualism of mycobiont and photobiont that harbors diverse organisms including endolichenic fungi (ELF). Despite the taxonomic and ecological significance of ELF, no comparative investigation of an ELF community involving isolation of a pure culture and high-throughput sequencing has been conducted. Thus, we analyzed the ELF community in Parmotrema tinctorum by culture and metabarcoding. Alpha diversity of the ELF community was notably greater in metabarcoding than in culture-based analysis. Taxonomic proportions of the ELF community estimated by metabarcoding and by culture analyses showed remarkable differences: Sordariomycetes was the most dominant fungal class in culture-based analysis, while Dothideomycetes was the most abundant in metabarcoding analysis. Thirty-seven operational taxonomic units (OTUs) were commonly observed by culture- and metabarcoding-based analyses but relative abundances differed: most of common OTUs were underrepresented in metabarcoding. The ELF community differed in lichen segments and thalli in metabarcoding analysis. Dissimilarity of ELF community intra lichen thallus increased with thallus segment distance; inter-thallus ELF community dissimilarity was significantly greater than intra-thallus ELF community dissimilarity. Finally, we tested how many fungal sequence reads would be needed to ELF diversity with relationship assays between numbers of lichen segments and saturation patterns of OTU richness and sample coverage. At least 6000 sequence reads per lichen thallus were sufficient for prediction of overall ELF community diversity and 50,000 reads per thallus were enough to observe rare taxa of ELF.     

A DNA barcode library for 5,200 German flies and midges (Insecta: Diptera) and its implications for metabarcoding‐based biomonitoring

This study summarizes results of a DNA barcoding campaign on German Diptera, involving analysis of 45,040 specimens. The resultant DNA barcode library includes records for 2,453 named species comprising a total of 5,200 barcode index numbers (BINs), including 2,700 COI haplotype clusters without species‐level assignment, so called “dark taxa.” Overall, 88 out of 117 families (75%) recorded from Germany were covered, representing more than 50% of the 9,544 known species of German Diptera. Until now, most of these families, especially the most diverse, have been taxonomically inaccessible. By contrast, within a few years this study provided an intermediate taxonomic system for half of the German Dipteran fauna, which will provide a useful foundation for subsequent detailed, integrative taxonomic studies. Using DNA extracts derived from bulk collections made by Malaise traps, we further demonstrate that species delineation using BINs and operational taxonomic units (OTUs) constitutes an effective method for biodiversity studies using DNA metabarcoding. As the reference libraries continue to grow, and gaps in the species catalogue are filled, BIN lists assembled by metabarcoding will provide greater taxonomic resolution. The present study has three main goals: (a) to provide a DNA barcode library for 5,200 BINs of Diptera; (b) to demonstrate, based on the example of bulk extractions from a Malaise trap experiment, that DNA barcode clusters, labelled with globally unique identifiers (such as OTUs and/or BINs), provide a pragmatic, accurate solution to the “taxonomic impediment”; and (c) to demonstrate that interim names based on BINs and OTUs obtained through metabarcoding provide an effective method for studies on species‐rich groups that are usually neglected in biodiversity research projects because of their unresolved taxonomy.     

Quantitative multi‐locus metabarcoding and waggle dance interpretation reveal honey bee spring foraging patterns in Midwest agroecosystems

We explored the pollen foraging behaviour of honey bee colonies situated in the corn and soybean dominated agroecosystems of central Ohio over a month‐long period using both pollen metabarcoding and waggle dance inference of spatial foraging patterns. For molecular pollen analysis, we developed simple and cost‐effective laboratory and bioinformatics methods. Targeting four plant barcode loci (ITS2, rbcL, trnL and trnH), we implemented metabarcoding library preparation and dual‐indexing protocols designed to minimize amplification biases and index mistagging events. We constructed comprehensive, curated reference databases for hierarchical taxonomic classification of metabarcoding data and used these databases to train the metaxa 2 DNA sequence classifier. Comparisons between morphological and molecular palynology provide strong support for the quantitative potential of multi‐locus metabarcoding. Results revealed consistent foraging habits between locations and show clear trends in the phenological progression of honey bee spring foraging in these agricultural areas. Our data suggest that three key taxa, woody Rosaceae such as pome fruits and hawthorns, Salix, and Trifolium provided the majority of pollen nutrition during the study. Spatially, these foraging patterns were associated with a significant preference for forests and tree lines relative to herbaceous land cover and nonflowering crop fields.     

Unlocking biodiversity and conservation studies in high‐diversity environments using environmental DNA (eDNA): A test with Guianese freshwater fishes

Determining the species compositions of local assemblages is a prerequisite to understanding how anthropogenic disturbances affect biodiversity. However, biodiversity measurements often remain incomplete due to the limited efficiency of sampling methods. This is particularly true in freshwater tropical environments that host rich fish assemblages, for which assessments are uncertain and often rely on destructive methods. Developing an efficient and nondestructive method to assess biodiversity in tropical freshwaters is highly important. In this study, we tested the efficiency of environmental DNA (eDNA) metabarcoding to assess the fish diversity of 39 Guianese sites. We compared the diversity and composition of assemblages obtained using traditional and metabarcoding methods. More than 7,000 individual fish belonging to 203 Guianese fish species were collected by traditional sampling methods, and ~17 million reads were produced by metabarcoding, among which ~8 million reads were assigned to 148 fish taxonomic units, including 132 fish species. The two methods detected a similar number of species at each site, but the species identities partially matched. The assemblage compositions from the different drainage basins were better discriminated using metabarcoding, revealing that while traditional methods provide a more complete but spatially limited inventory of fish assemblages, metabarcoding provides a more partial but spatially extensive inventory. eDNA metabarcoding can therefore be used for rapid and large‐scale biodiversity assessments, while at a local scale, the two approaches are complementary and enable an understanding of realistic fish biodiversity.     

Comparison of destructive and nondestructive DNA extraction methods for the metabarcoding of arthropod bulk samples

DNA metabarcoding is routinely used for biodiversity assessment, in particular targeting highly diverse groups for which limited taxonomic expertise is available. Various protocols are currently in use, although standardization is key to its application in large-scale monitoring. DNA metabarcoding of arthropod bulk samples can be conducted either destructively from sample tissue, or nondestructively from sample fixative or lysis buffer. Nondestructive methods are highly desirable for the preservation of sample integrity but have yet to be experimentally evaluated in detail. Here, we compare diversity estimates from 14 size-sorted Malaise trap samples processed consecutively with three nondestructive approaches (one using fixative ethanol and two using lysis buffers) and one destructive approach (using homogenized tissue). Extraction from commercial lysis buffer yielded comparable species richness and high overlap in species composition to the ground tissue extracts. A significantly divergent community was detected from preservative ethanol-based DNA extraction. No consistent trend in species richness was found with increasing incubation time in lysis buffer. These results indicate that nondestructive DNA extraction from incubation in lysis buffer could provide a comparable alternative to destructive approaches with the added advantage of preserving the specimens for postmetabarcoding taxonomic work but at a higher cost per sample.     

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.     

Ichthyoplankton metabarcoding: An efficient tool for early detection of invasive species establishment

Detection of invasive species is critical for management but is often limited by challenges associated with capture, processing and identification of early life stages. DNA metabarcoding facilitates large-scale monitoring projects to detect establishment early. Here, we test the use of DNA metabarcoding to monitor invasive species by sequencing over 5000 fishes in bulk ichthyoplankton samples (larvae and eggs) from four rivers of ecological and cultural importance in southern Canada. We were successful in detecting species known from each river and three invasive species in two of the four rivers. This includes the first detection of early life-stage rudd in the Credit River. We evaluated whether sampling gear affected the detection of invasive species and estimates of species richness, and found that light traps outperform bongo nets in both cases. We also found that the primers used for the amplification of target sequences and the number of sequencing reads generated per sample affect the consistency of species detections. However, these factors have less impact on detections and species richness estimates than the number of samples collected and analysed. Our analyses also show that incomplete reference databases can result in incorrectly attributing DNA sequences to invasive species. Overall, we conclude that DNA metabarcoding is an efficient tool for monitoring the early establishment of invasive species by detecting evidence of reproduction but requires careful consideration of sampling design and the primers used to amplify, sequence and classify the diversity of native and potentially invasive species.     

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.     

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

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A practical guide to DNA metabarcoding for entomological ecologists

1. DNA metabarcoding is a cost-effective species identification approach with great potential to assist entomological ecologists. This review presents a practical guide to help entomological ecologists design their own DNA metabarcoding studies and ensure that sound ecological conclusions can be obtained. 2. The review considers approaches to field sampling, laboratory work, and bioinformatic analyses, with the aim of providing the background knowledge needed to make decisions at each step of a DNA metabarcoding workflow. 3. Although most conventional sampling methods can be adapted to DNA metabarcoding, this review highlights techniques that will ensure suitable DNA preservation during field sampling and laboratory storage. The review also calls for a greater understanding of the occurrence, transportation, and deposition of environmental DNA when applying DNA metabarcoding approaches for different ecosystems. 4. Accurate species detection with DNA metabarcoding needs to consider biases introduced during DNA extraction and PCR amplification, cross-contamination resulting from inappropriate amplicon library preparation, and downstream bioinformatic analyses. Quantifying species abundance with DNA metabarcoding is in its infancy, yet recent studies demonstrate promise for estimating relative species abundance from DNA sequencing reads. 5. Given that bioinformatics is one of the biggest hurdles for researchers new to DNA metabarcoding, several useful graphical user interface programs are recommended for sequence data processing, and the application of emerging sequencing technologies is discussed.     

Seasonal dynamics of riverine fish communities using eDNA

As fish communities are a major concern in rivers ecosystems, we investigated if their environmental (e)DNA signals vary according to the sampling period or hydromorphological conditions. Three rivers were studied over a year using eDNA metabarcoding approach. The majority of the species (c. 80%) were detected all year round in two rivers having similar hydromorphological conditions, whereas in the river affected by an upstream lake waterflow, more species were detected sporadically (42%). For all the rivers, in more than 98% of the occasional detections, the reads abundance represented <0.4% of the total reads per site and per sampling session. Even if the majority of the fish communities remained similar over the year for each of the three rivers, specific seasonal patterns were observed. We studied if the waterflow or the reproduction period had an effect on the observed dynamics. Waterflow, which influences eDNA downstream transportation, had a global influence in taxonomic richness, while the fishes' reproductive period had only an influence on certain species. Our results may help selecting the best sampling strategy according to research objectives. To study fish communities at local scale, seasons of low waterflow periods are recommended. This particularly helps to restraint effects of external eDNA coming from connections with other aquatic environment (tributaries, lakes, wetlands, sewage effluents, etc.). To obtain a more integrative overview of the fish community living in a river basin, high waterflow or breeding seasons are preferable for enhancing species detection probability, especially for rare species.     

ITS all right mama: investigating the formation of chimeric sequences in the ITS2 region by DNA metabarcoding analyses of fungal mock communities of different complexities

The formation of chimeric sequences can create significant methodological bias in PCR‐based DNA metabarcoding analyses. During mixed‐template amplification of barcoding regions, chimera formation is frequent and well documented. However, profiling of fungal communities typically uses the more variable rDNA region ITS. Due to a larger research community, tools for chimera detection have been developed mainly for the 16S/18S markers. However, these tools are widely applied to the ITS region without verification of their performance. We examined the rate of chimera formation during amplification and 454 sequencing of the ITS2 region from fungal mock communities of different complexities. We evaluated the chimera detecting ability of two common chimera‐checking algorithms: perseus and uchime . Large proportions of the chimeras reported were false positives. No false negatives were found in the data set. Verified chimeras accounted for only 0.2% of the total ITS2 reads, which is considerably less than what is typically reported in 16S and 18S metabarcoding analyses. Verified chimeric ‘parent sequences’ had significantly higher per cent identity to one another than to random members of the mock communities. Community complexity increased the rate of chimera formation. GC content was higher around the verified chimeric break points, potentially facilitating chimera formation through base pair mismatching in the neighbouring regions of high similarity in the chimeric region. We conclude that the hypervariable nature of the ITS region seems to buffer the rate of chimera formation in comparison with other, less variable barcoding regions, due to shorter regions of high sequence similarity.     

Replicate DNA metabarcoding can discriminate seasonal and spatial abundance shifts in river macroinvertebrate assemblages

The delivery of consistent and accurate fine-resolution data on biodiversity using metabarcoding promises to improve environmental assessment and research. Whilst this approach is a substantial improvement upon traditional techniques, critics note that metabarcoding data are suitable for establishing taxon occurrence, but not abundance. We propose a novel hierarchical approach to recovering abundance information from metabarcoding, and demonstrate this technique using benthic macroinvertebrates. To sample a range of abundance structures without introducing additional changes in composition, we combined seasonal surveys with fish-exclusion experiments at Catamaran Brook in northern New Brunswick, Canada. Five monthly surveys collected 31 benthic samples for DNA metabarcoding divided between caged and control treatments. A further six samples per survey were processed using traditional morphological identification for comparison. By estimating the probability of detecting a single individual, multispecies abundance models infer changes in abundance based on changes in detection frequency. Using replicate detections of 184 genera (and 318 species) from metabarcoding samples, our analysis identified changes in abundance arising from both seasonal dynamics and the exclusion of fish predators. Counts obtained from morphological samples were highly variable, a feature that limited the opportunity for more robust comparison, and emphasizing the difficulty standard methods also face to detect changes in abundance. Our approach is the first to demonstrate how quantitative estimates of abundance can be made using metabarcoding, both among species within sites as well as within species among sites. Many samples are required to capture true abundance patterns, particularly in streams where counts are highly variable, but few studies can afford to process entire samples. Our approach allows study of responses across whole communities, and at fine taxonomic resolution. We discuss how ecological studies can use additional sampling to capture changes in abundance at fine resolution, and how this can complement broad-scale biomonitoring using DNA metabarcoding.     

Extracting abundance information from DNA-based data

The accurate extraction of species-abundance information from DNA-based data (metabarcoding, metagenomics) could contribute usefully to diet analysis and food-web reconstruction, the inference of species interactions, the modelling of population dynamics and species distributions, the biomonitoring of environmental state and change, and the inference of false positives and negatives. However, multiple sources of bias and noise in sampling and processing combine to inject error into DNA-based data sets. To understand how to extract abundance information, it is useful to distinguish two concepts. (i) Within-sample across-species quantification describes relative species abundances in one sample. (ii) Across-sample within-species quantification describes how the abundance of each individual species varies from sample to sample, such as over a time series, an environmental gradient or different experimental treatments. First, we review the literature on methods to recover across-species abundance information (by removing what we call “species pipeline biases”) and within-species abundance information (by removing what we call “pipeline noise”). We argue that many ecological questions can be answered with just within-species quantification, and we therefore demonstrate how to use a “DNA spike-in” to correct for pipeline noise and recover within-species abundance information. We also introduce a model-based estimator that can be used on data sets without a physical spike-in to approximate and correct for pipeline noise.     

Quantification of mesocosm fish and amphibian species diversity via environmental DNA metabarcoding

Freshwater fauna are particularly sensitive to environmental change and disturbance. Management agencies frequently use fish and amphibian biodiversity as indicators of ecosystem health and a way to prioritize and assess management strategies. Traditional aquatic bioassessment that relies on capture of organisms via nets, traps and electrofishing gear typically has low detection probabilities for rare species and can injure individuals of protected species. Our objective was to determine whether environmental DNA (eDNA) sampling and metabarcoding analysis can be used to accurately measure species diversity in aquatic assemblages with differing structures. We manipulated the density and relative abundance of eight fish and one amphibian species in replicated 206‐L mesocosms. Environmental DNA was filtered from water samples, and six mitochondrial gene fragments were Illumina‐sequenced to measure species diversity in each mesocosm. Metabarcoding detected all nine species in all treatment replicates. Additionally, we found a modest, but positive relationship between species abundance and sequencing read abundance. Our results illustrate the potential for eDNA sampling and metabarcoding approaches to improve quantification of aquatic species diversity in natural environments and point the way towards using eDNA metabarcoding as an index of macrofaunal species abundance.