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.     

DNA metabarcoding of airborne pollen: new protocols for improved taxonomic identification of environmental samples

Metabarcoding is a promising DNA-based method for identifying airborne pollen from environmental samples with advantages over microscopic methods. Sample preparation and DNA extraction are of fundamental importance for obtaining an optimal DNA yield. Currently, there is no standard procedure for these steps, especially for gravimetric pollen samplers. Therefore, the aim of this study was to develop protocols for processing environmental samples for pollen DNA extraction and for metabarcoding analysis and to assess the efficacy of these protocols for the taxonomic assignment of airborne pollen collected by gravimetric (Tauber trap) and volumetric (Hirst-type trap) samplers. Protocols were tested across an increasing complexity of samples, from pure single-species pollen to environmental multi-species samples. A short fragment (about 150 base pairs) of the chloroplast trnL gene was amplified using universal primers for plants. After PCR amplification, amplicons were Sanger-sequenced and taxonomic assignment was accomplished by comparison with a custom-made reference database including chloroplast DNA sequences from most of the anemophilous taxa occurring in the study area (Trentino, northern Italy), representing 46 plant families. Using the classical morphological pollen analysis as a benchmark, we show that DNA metabarcoding is efficient and applicable even in complex samples, provided that protocols for sample preparation, DNA extraction, and metabarcoding analysis are carefully optimized.     

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.     

Biodiversity of pollen in indoor air samples as revealed by DNA metabarcoding

We conducted DNA metabarcoding (based on the nuclear ITS2 region) to characterize indoor pollen samples (possibly accompanied by other plant fragments) and to discover whether there are seasonal changes in their taxonomic diversity. It was shown that DNA metabarcoding has potential to allow a good discovery of taxonomic diversity. The number of spermatophyte families and genera varied greatly among sampling sites (pooled results per building) and times, between 9–40 and 10–66, respectively. Comparable Shannon's diversity indices equaled 0.33–2.76 and 0.94–3.16. The total number of spermatophyte genera found during the study was 187, of which 43.9, 39.6, 7.5 and 9.1% represented wild, garden/crop and indoor house plants, and non‐domestic fruit or other plant material, respectively. Comparable proportions of individual sequences equaled 77.4, 18.8, 2.7 and 1.1%, respectively. When comparing plant diversities and taxonomic composition among buildings or between seasons, no obvious pattern was detected, except for the second summer, when pollen coming from outdoors was highly dominant and the proportions of likely allergens, birch, grass, alder and mugwort pollen, were very high. The average pairwise values of Sørensen_Chao indices that were used to compare similarities for taxon composition between samples among the samples from the two university buildings, two nurseries and farmhouse equaled 0.514, 0.109, 0.564, 0.865 and 0.867, respectively, while the mean similarity index for all samples was 0.524. Cleaning frequency may strongly contribute to the observed diversity. The discovery of considerable diversities, including pollen coming from outside, in both winter and summer shows that substantial amounts of pollen produced in summer enter buildings and stay there throughout the year.     

Using DNA Metabarcoding to Identify the Floral Composition of Honey: A New Tool for Investigating Honey Bee Foraging Preferences

Identifying the floral composition of honey provides a method for investigating the plants that honey bees visit. We compared melissopalynology, where pollen grains retrieved from honey are identified morphologically, with a DNA metabarcoding approach using the rbcL DNA barcode marker and 454-pyrosequencing. We compared nine honeys supplied by beekeepers in the UK. DNA metabarcoding and melissopalynology were able to detect the most abundant floral components of honey. There was 92% correspondence for the plant taxa that had an abundance of over 20%. However, the level of similarity when all taxa were compared was lower, ranging from 22–45%, and there was little correspondence between the relative abundance of taxa found using the two techniques. DNA metabarcoding provided much greater repeatability, with a 64% taxa match compared to 28% with melissopalynology. DNA metabarcoding has the advantage over melissopalynology in that it does not require a high level of taxonomic expertise, a greater sample size can be screened and it provides greater resolution for some plant families. However, it does not provide a quantitative approach and pollen present in low levels are less likely to be detected. We investigated the plants that were frequently used by honey bees by examining the results obtained from both techniques. Plants with a broad taxonomic range were detected, covering 46 families and 25 orders, but a relatively small number of plants were consistently seen across multiple honey samples. Frequently found herbaceous species were Rubus fruticosus, Filipendula ulmaria, Taraxacum officinale, Trifolium spp., Brassica spp. and the non-native, invasive, Impatiens glandulifera. Tree pollen was frequently seen belonging to Castanea sativa, Crataegus monogyna and species of Malus, Salix and Quercus. We conclude that although honey bees are considered to be supergeneralists in their foraging choices, there are certain key species or plant groups that are particularly important in the honey bees environment. The reasons for this require further investigation in order to better understand honey bee nutritional requirements. DNA metabarcoding can be easily and widely used to investigate floral visitation in honey bees and can be adapted for use with other insects. It provides a starting point for investigating how we can better provide for the insects that we rely upon for pollination.     

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.     

Detecting flying insects using car nets and DNA metabarcoding

Monitoring insects across space and time is challenging, due to their vast taxonomic and functional diversity. This study demonstrates how nets mounted on rooftops of cars (car nets) and DNA metabarcoding can be applied to sample flying insect richness and diversity across large spatial scales within a limited time period. During June 2018, 365 car net samples were collected by 151 volunteers during two daily time intervals on 218 routes in Denmark. Insect bulk samples were processed with a DNA metabarcoding protocol to estimate taxonomic composition, and the results were compared to known flying insect richness and occurrence data. Insect and hoverfly richness and diversity were assessed across biogeographic regions and dominant land cover types. We detected 15 out of 19 flying insect orders present in Denmark, with high proportions of especially Diptera compared to Danish estimates, and lower insect richness and diversity in urbanized areas. We detected 319 species not known for Denmark and 174 species assessed in the Danish Red List. Our results indicate that the methodology can assess the flying insect fauna at large spatial scales to a wide extent, but may be, like other methods, biased towards certain insect orders.     

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.     

Pollen metabarcoding as a tool for tracking long‐distance insect migrations

Insects account for a large portion of Earth's biodiversity and are key players for ecosystems, notably as pollinators. While insect migration is suspected to represent a natural phenomenon of major importance, remarkably little is known about it, except for a few flagship species. The reason for this situation is mainly due to technical limitations in the study of insect movement. Here, we propose using metabarcoding of pollen carried by insects as a method for tracking their migrations. We developed a flexible and simple protocol allowing efficient multiplexing and not requiring DNA extraction, one of the most time‐consuming part of metabarcoding protocols, and apply this method to the study of the long‐distance migration of the butterfly Vanessa cardui, an emerging model for insect migration. We collected 47 butterfly samples along the Mediterranean coast of Spain in spring and performed metabarcoding of pollen collected from their bodies to test for potential arrivals from the African continent. In total, we detected 157 plant species from 23 orders, most of which (82.8%) were insect‐pollinated. Taxa present in Africa–Arabia represented 73.2% of our data set, and 19.1% were endemic to this region, strongly supporting the hypothesis that migratory butterflies colonize southern Europe from Africa in spring. Moreover, our data suggest that a northwards trans‐Saharan migration in spring is plausible for early arrivals (February) into Europe, as shown by the presence of Saharan floristic elements. Our results demonstrate the possibility of regular insect‐mediated transcontinental pollination, with potential implications for ecosystem functioning, agriculture and plant phylogeography.     

利用宏DNA条形码研究浮游动物多样性——以鸭绿江口为例

为评价宏DNA条形码技术在我国海洋生物多样性监测中的应用潜力,采集了22份鸭绿江口浮游动物样品,分别利用宏条形码分子鉴定和形态鉴定方法对优势类群桡足类进行多样性的比较研究。结果显示:(1)利用宏条形码分子鉴定方法共鉴定出4目23科32属229个操作分类单元(Operational Taxonomic Units, OTUs),形态方法共鉴定出3目5科5属6种;同时,利用形态鉴定得到的分类阶元多数(目:100%、科:80%、属:80%)能用宏条形码分子鉴定方法鉴定出来,而宏条形码分子鉴定方法鉴定得到的分类阶元多数(目:25%、科:83%、属:88%)却未能用形态鉴定出来,表明宏条形码分子鉴定方法在鉴定物种丰富度方面具有明显优势。(2)利用宏条形码分子鉴定与形态鉴定桡足类的多样性指数呈显著的一致性(r=0.524,P=0.024),表明宏条形码鉴定方法与形态方法在评价物种多样性方面具有较好的可比性。本研究表明宏条形码分子鉴定方法在我国海洋浮游动物业务化监测中具有较高的应用潜力。     

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.     

Construction,validation, and application of nocturnal pollen transport networks in an agro‐ecosystem: a comparison using light microscopy and DNA metabarcoding

1. Moths are globally relevant as pollinators but nocturnal pollination remains poorly understood. Plant–pollinator interaction networks are traditionally constructed using either flower‐visitor observations or pollen‐transport detection using microscopy. Recent studies have shown the potential of DNA metabarcoding for detecting and identifying pollen‐transport interactions. However, no study has directly compared the realised observations of pollen‐transport networks between DNA metabarcoding and conventional light microscopy. 2. Using matched samples of nocturnal moths, we constructed pollen‐transport networks using two methods: light microscopy and DNA metabarcoding. Focussing on the feeding mouthparts of moths, we developed and provide reproducible methods for merging DNA metabarcoding and ecological network analysis to better understand species interactions. 3. DNA metabarcoding detected pollen on more individual moths, and detected multiple pollen types on more individuals than microscopy, although the average number of pollen types per individual was unchanged. However, after aggregating individuals of each species, metabarcoding detected more interactions per moth species. Pollen‐transport network metrics differed between methods because of variation in the ability of each to detect multiple pollen types per moth and to separate morphologically similar or related pollen. We detected unexpected but plausible moth–plant interactions with metabarcoding, revealing new detail about nocturnal pollination systems. 4. The nocturnal pollination networks observed using metabarcoding and microscopy were similar yet distinct, with implications for network ecologists. Comparisons between networks constructed using metabarcoding and traditional methods should therefore be treated with caution. Nevertheless, the potential applications of metabarcoding for studying plant–pollinator interaction networks are encouraging, especially when investigating understudied pollinators such as moths.     

Mass-flowering crops enhance wild bee abundance

Although agricultural habitats can provide enormous amounts of food resources for pollinator species, links between agricultural and (semi-)natural habitats through dispersal and foraging movements have hardly been studied. In 67 study sites, we assessed the interactions between mass-flowering oilseed rape fields and semi-natural grasslands at different spatial scales, and their effects on the number of brood cells of a solitary cavity-nesting bee. The probability that the bee Osmia bicornis colonized trap nests in oilseed rape fields increased from 12 to 59 % when grassland was nearby, compared to fields isolated from grassland. In grasslands, the number of brood cells of O. bicornis in trap nests was 55 % higher when adjacent to oilseed rape compared to isolated grasslands. The percentage of oilseed rape pollen in the larval food was higher in oilseed rape fields and grasslands adjacent to oilseed rape than in isolated grasslands. In both oilseed rape fields and grasslands, the number of brood cells was positively correlated with the percentage of oilseed rape pollen in the larval food. We show that mass-flowering agricultural habitats—even when they are intensively managed—can strongly enhance the abundance of a solitary bee species nesting in nearby semi-natural habitats. Our results suggest that positive effects of agricultural habitats have been underestimated and might be very common (at least) for generalist species in landscapes consisting of a mixture of agricultural and semi-natural habitats. These effects might also have—so far overlooked—implications for interspecific competition and mutualistic interactions in semi-natural habitats.     

Taking eDNA underground: Factors affecting eDNA detection of subterranean fauna in groundwater

Stygofauna are aquatic fauna that have evolved to live underground. The impacts of anthropogenic climate change, extraction and pollution on groundwater pose major threats to groundwater health, prompting the need for efficient and reliable means to detect and monitor stygofaunal communities. Conventional survey techniques for these species rely on morphological identification and can be biased, labour-intensive and often indeterminate to lower taxonomic levels. By contrast, environmental DNA (eDNA)-based methods have the potential to dramatically improve on existing stygofaunal survey methods in a large range of habitats and for all life stages, reducing the need for the destructive manual collection of often critically endangered species or for specialized taxonomic expertise. We compared eDNA and haul-net samples collected in 2020 and 2021 from 19 groundwater bores and a cave on Barrow Island, northwest Western Australia, and assessed how sampling factors influenced the quality of eDNA detection of stygofauna. The two detection methods were complementary; eDNA metabarcoding was able to detect soft-bodied taxa and fish often missed by nets, but only detected seven of the nine stygofaunal crustacean orders identified from haul-net specimens. Our results also indicated that eDNA metabarcoding could detect 54%–100% of stygofauna from shallow-water samples and 82%–90% from sediment samples. However, there was significant variation in stygofaunal diversity between sample years and sampling types. The findings of this study demonstrate that haul-net sampling has a tendency to underestimate stygofaunal diversity and that eDNA metabarcoding of groundwater can substantially improve the efficiency of stygofaunal surveys.     

Pollen movement to flowering canopies of pistillate individuals of three rain forest tree species in tropical Australia

This study measured the quantities of effective pollen vectors and their pollen loads arriving at the canopies of dioecious tropical rain forest trees in north-east Queensland. Population flowering synchrony, effective pollinator populations and pollen loads transferred between staminate and pistillate trees were compared among three insect-pollinated tree species. All three were visited by a wide range of insects, 75% of which (mostly 3–6 mm long) carried conspecific pollen. Fewer than 8% of individual insects were found to be carrying single-species pollen exclusively and none could be described as specialist pollen foragers. The introduced honeybee carried greater quantities of pollen than any native species but was not necessarily a reliable pollinator. The brief flowering periods in Neolitsea dealbata (3–4 weeks) and Litsea leefeana (4–5 weeks) populations were synchronized among individuals. Flowering in the Diospyros pentamera population extended over 15 weeks and most individuals were in flower for most of this period. Staminate trees began flowering earlier, produced more flowers and attracted relatively more insects than did pistillate trees, suggesting a density-dependent response of pollinators to flowering performance. Pollen was trapped in greater quantities on insects at staminate trees than at pistillate trees. Insect numbers increased at peak flowering periods and Diptera were the most abundant flower visitors. Anthophilous Coleoptera were more numerous at staminate than at pistillate trees in all three tree species populations. Larger quantities of pollen were mobilized during peak flowering times although the greatest quantities were transferred to pistillate canopies towards the end of the population flowering periods. Diptera carried pollen more often to pistillate N. dealbata and L. leefeana trees than did other groups whereas Coleoptera carried pollen more often to pistillate D. pentamera trees. The two contrasting flowering performances in the three tree species are discussed with reference to mechanisms that facilitate pollen transfer between staminate and pistillate trees.     

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).     

Pollen transport differs among bees and flies in a human‐modified landscape

Aim Dispersal distances of insect pollinators are critical in defining their contribution to landscape‐wide pollen movement and ultimately gene flow in natural and agricultural systems. We ask whether bee and fly pollinator taxa differ in their dispersal distances and transport of viable pollen in a human‐modified system. Location Canterbury and Otago region, South Island, New Zealand. Methods We captured pollen‐carrying insects travelling outside of a model mass‐flowering agricultural crop, Brassica rapa, using insect flight intercept traps at five distances (0, 100, 200, 300 and 400 m) from the pollen source. We examined pollen loads and pollen viability to determine whether pollen transport distance and viability differ among pollinator taxa. Results A total of 5453 insects were collected of which 717 individuals from 26 insect taxa were positively identified as dispersing pollen up to 400 m from the source. These taxa consisted of four species from two bee families (Hymenoptera: Apidae and Halictidae), and eight species from four fly families (Diptera: Bibiondae, Stratiomyidae, Syrphidae and Tachinidae). Apidae generally carried higher pollen loads and more viable pollen than most fly taxa. Taxa in the fly families Stratiomyidae and Syrphidae, however, carried pollen to 400 m, which is further than both bee families. Main conclusions A diverse array of wild and managed flower visitors can transport viable pollen from a pollen source to at least 400 m. Knowledge of the differences in transport distances among generalist pollinators in human‐modified environments is crucial to understand the potential extent to which (1) pollen transport can facilitate gene flow and (2) unwanted hybridization may occur between crops and related weeds.     

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.     

Optimization and validation of a cost‐effective protocol for biosurveillance of invasive alien species

Environmental DNA (eDNA) metabarcoding has revolutionized biodiversity monitoring and invasive pest biosurveillance programs. The introduction of insect pests considered invasive alien species (IAS) into a non‐native range poses a threat to native plant health. The early detection of IAS can allow for prompt actions by regulating authorities, thereby mitigating their impacts. In the present study, we optimized and validated a fast and cost‐effective eDNA metabarcoding protocol for biosurveillance of IAS and characterization of insect and microorganism diversity. Forty‐eight traps were placed, following the CFIA''s annual forest insect trapping survey, at four locations in southern Ontario that are high risk for forest IAS. We collected insects and eDNA samples using Lindgren funnel traps that contained a saturated salt (NaCl) solution in the collection jar. Using cytochrome c oxidase I (COI) as a molecular marker, a modified Illumina protocol effectively identified 2,535 Barcode Index Numbers (BINs). BINs were distributed among 57 Orders and 304 Families, with the vast majority being arthropods. Two IAS (Agrilus planipennis and Lymantria dispar) are regulated by the Canadian Food Inspection Agency (CFIA) as plant health pests, are known to occur in the study area, and were identified through eDNA in collected traps. Similarly, using 16S ribosomal RNA and nuclear ribosomal internal transcribed spacer (ITS), five bacterial and three fungal genera, which contain species of regulatory concern across several Canadian jurisdictions, were recovered from all sampling locations. Our study results reaffirm the effectiveness and importance of integrating eDNA metabarcoding as part of identification protocols in biosurveillance programs.     

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.