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.     

DNA宏条形码技术在鸟类食性分析中的运用

鸟类在全球广泛分布,不同鸟类物种利用的食物类群存在很大差异,而食性研究是动物营养学和生态学领域的重要研究内容。本文对一些传统鸟类食性鉴别方式及其不足进行回顾,传统鸟类食性鉴别方式包含扎颈法、剖胃法、粪便收集法、相机记录法等。随着测序技术的高速发展,DNA宏条形码技术出现,并广泛应用于动物食性研究。近些年来,该技术也被应用于鸟类食性研究中。本文综述了DNA条形码和DNA宏条形码的操作原理和条件,对鸟类食性研究中的DNA条形码与引物的选择做了详细介绍。对比传统鉴别方法,DNA宏条形码技术降低了物种鉴定难度,减少了人为影响因素,提高了目标样本中物种的鉴定效率,能对粪便、胃容物等混合或不成型样本进行分析。另一方面,在扩增多物种混合的DNA样品中的目标片段时,可能出现偏离,造成结果的不确定性,并且难以根据结果得出较准确各食物组分的比例。未来在使用宏条形码技术对鸟类食性的分析中,可结合其他方法改善对食物的量化以及食物属性的判断。     

基于DNA宏条形码技术的蓝彩带蜂粉源植物多样性研究

蓝彩带蜂(Nomia chalybeate Smith, 1875)隶属隧蜂科彩带蜂属,是一种典型的广访花性野生蜜蜂,广泛分布于我国东部地区及日本、韩国、印度、缅甸等国家。本研究基于我国东部9个省份18个不同样地20份蓝彩带蜂蜂粮样本,包括安徽省(AHGZ、AHJZ)、重庆市(CQSMS、CQWS)、福建省(FJSM)、广西省(GXHP、GXLZ)、湖南省(HNHY、HNQY)、海南省(HNLS、HNWC)、江西省(JXGX、JXJG6、JXJG8、JXQY6、JXQY8、JXYZ)、山东省(SDLL)、浙江省(ZJCS)。利用DNA宏条形码研究该蜂粉源植物的多样性,为全面掌握该蜂的粉源植物及保护策略提供理论依据。结果表明该蜂粉源植物共涉及47科,99属,124种,其中黄荆(Vitex negundo)是最优势种、其次是罗伞树(Ardisia quinquegona)和山莓(Rubus corchorifolius)。Alpha多样性指数分析显示：SDLL样本的物种丰富度和多样性最高,FJSM样本的丰富度和多样性最低。不同样地的粉源植物多样性具有差异,但该蜂同一样地不同时期的粉源植物多...     

Sorting things out: Assessing effects of unequal specimen biomass on DNA metabarcoding

Environmental bulk samples often contain many different taxa that vary several orders of magnitude in biomass. This can be problematic in DNA metabarcoding and metagenomic high‐throughput sequencing approaches, as large specimens contribute disproportionately high amounts of DNA template. Thus, a few specimens of high biomass will dominate the dataset, potentially leading to smaller specimens remaining undetected. Sorting of samples by specimen size (as a proxy for biomass) and balancing the amounts of tissue used per size fraction should improve detection rates, but this approach has not been systematically tested. Here, we explored the effects of size sorting on taxa detection using two freshwater macroinvertebrate bulk samples, collected from a low‐mountain stream in Germany. Specimens were morphologically identified and sorted into three size classes (body size < 2.5 × 5, 5 × 10, and up to 10 × 20 mm). Tissue powder from each size category was extracted individually and pooled based on tissue weight to simulate samples that were not sorted by biomass (“Unsorted”). Additionally, size fractions were pooled so that each specimen contributed approximately equal amounts of biomass (“Sorted”). Mock samples were amplified using four different DNA metabarcoding primer sets targeting the Cytochrome c oxidase I (COI) gene. Sorting taxa by size and pooling them proportionately according to their abundance lead to a more equal amplification of taxa compared to the processing of complete samples without sorting. The sorted samples recovered 30% more taxa than the unsorted samples at the same sequencing depth. Our results imply that sequencing depth can be decreased approximately fivefold when sorting the samples into three size classes and pooling by specimen abundance. Even coarse size sorting can substantially improve taxa detection using DNA metabarcoding. While high‐throughput sequencing will become more accessible and cheaper within the next years, sorting bulk samples by specimen biomass or size is a simple yet efficient method to reduce current sequencing costs.     

DNA metabarcoding and the cytochrome c oxidase subunit I marker: not a perfect match

DNA metabarcoding enables efficient characterization of species composition in environmental DNA or bulk biodiversity samples, and this approach is making significant and unique contributions in the field of ecology. In metabarcoding of animals, the cytochrome c oxidase subunit I (COI) gene is frequently used as the marker of choice because no other genetic region can be found in taxonomically verified databases with sequences covering so many taxa. However, the accuracy of metabarcoding datasets is dependent on recovery of the targeted taxa using conserved amplification primers. We argue that COI does not contain suitably conserved regions for most amplicon-based metabarcoding applications. Marker selection deserves increased scrutiny and available marker choices should be broadened in order to maximize potential in this exciting field of research.     

Quantitative DNA metabarcoding: improved estimates of species proportional biomass using correction factors derived from control material

DNA metabarcoding is a powerful new tool allowing characterization of species assemblages using high‐throughput amplicon sequencing. The utility of DNA metabarcoding for quantifying relative species abundances is currently limited by both biological and technical biases which influence sequence read counts. We tested the idea of sequencing 50/50 mixtures of target species and a control species in order to generate relative correction factors (RCFs) that account for multiple sources of bias and are applicable to field studies. RCFs will be most effective if they are not affected by input mass ratio or co‐occurring species. In a model experiment involving three target fish species and a fixed control, we found RCFs did vary with input ratio but in a consistent fashion, and that 50/50 RCFs applied to DNA sequence counts from various mixtures of the target species still greatly improved relative abundance estimates (e.g. average per species error of 19 ± 8% for uncorrected vs. 3 ± 1% for corrected estimates). To demonstrate the use of correction factors in a field setting, we calculated 50/50 RCFs for 18 harbour seal (Phoca vitulina) prey species (RCFs ranging from 0.68 to 3.68). Applying these corrections to field‐collected seal scats affected species percentages from individual samples (Δ 6.7 ± 6.6%) more than population‐level species estimates (Δ 1.7 ± 1.2%). Our results indicate that the 50/50 RCF approach is an effective tool for evaluating and correcting biases in DNA metabarcoding studies. The decision to apply correction factors will be influenced by the feasibility of creating tissue mixtures for the target species, and the level of accuracy needed to meet research objectives.     

Species‐level biodiversity assessment using marine environmental DNA metabarcoding requires protocol optimization and standardization

DNA extraction from environmental samples (environmental DNA; eDNA) for metabarcoding‐based biodiversity studies is gaining popularity as a noninvasive, time‐efficient, and cost‐effective monitoring tool. The potential benefits are promising for marine conservation, as the marine biome is frequently under‐surveyed due to its inaccessibility and the consequent high costs involved. With increasing numbers of eDNA‐related publications have come a wide array of capture and extraction methods. Without visual species confirmation, inconsistent use of laboratory protocols hinders comparability between studies because the efficiency of target DNA isolation may vary. We determined an optimal protocol (capture and extraction) for marine eDNA research based on total DNA yield measurements by comparing commonly employed methods of seawater filtering and DNA isolation. We compared metabarcoding results of both targeted (small taxonomic group with species‐level assignment) and universal (broad taxonomic group with genus/family‐level assignment) approaches obtained from replicates treated with the optimal and a low‐performance capture and extraction protocol to determine the impact of protocol choice and DNA yield on biodiversity detection. Filtration through cellulose‐nitrate membranes and extraction with Qiagen's DNeasy Blood & Tissue Kit outperformed other combinations of capture and extraction methods, showing a ninefold improvement in DNA yield over the poorest performing methods. Use of optimized protocols resulted in a significant increase in OTU and species richness for targeted metabarcoding assays. However, changing protocols made little difference to the OTU and taxon richness obtained using universal metabarcoding assays. Our results demonstrate an increased risk of false‐negative species detection for targeted eDNA approaches when protocols with poor DNA isolation efficacy are employed. Appropriate optimization is therefore essential for eDNA monitoring to remain a powerful, efficient, and relatively cheap method for biodiversity assessments. For seawater, we advocate filtration through cellulose‐nitrate membranes and extraction with Qiagen's DNeasy Blood & Tissue Kit or phenol‐chloroform‐isoamyl for successful implementation of eDNA multi‐marker metabarcoding surveys.     

Management of DNA reference libraries for barcoding and metabarcoding studies with the R package refdb

DNA barcoding and metabarcoding are revolutionizing the study and survey of biodiversity. In order to assign taxonomic labels to the DNA sequence data retrieved, these methods are strongly dependent on comprehensive and accurate reference databases. Producing reliable databases linking biological sequences and taxonomic data can be—and often has been—done using mainstream tools such as spreadsheet software. However, spreadsheets quickly become insufficient when the amount of data increases to thousands of taxa and sequences to be matched, and validation operations become more complex and are error prone if done in a manual way. Thus, there is a clear need for providing scientists with user-friendly, reliable and powerful tools to manipulate and manage DNA reference databases in tractable, sound and efficient ways. Here, we introduce the R package refdb as an environment for semi-automatic and assisted construction of DNA reference libraries. The refdb package is a reference database manager offering a set of powerful functions to import, organize, clean, filter, audit and export the data. It is broadly applicable in metabarcoding data generally obtained in biodiversity and biomonitoring studies. We present the main features of the package and outline how refdb can speed up reference database generation, management and handling, and thus contribute to standardization and repeatability in barcoding and metabarcoding studies.     

Efficient and sensitive identification and quantification of airborne pollen using next‐generation DNA sequencing

Pollen monitoring is an important and widely used tool in allergy research and creation of awareness in pollen‐allergic patients. Current pollen monitoring methods are microscope‐based, labour intensive and cannot identify pollen to the genus level in some relevant allergenic plant groups. Therefore, a more efficient, cost‐effective and sensitive method is needed. Here, we present a method for identification and quantification of airborne pollen using DNA sequencing. Pollen is collected from ambient air using standard techniques. DNA is extracted from the collected pollen, and a fragment of the chloroplast gene trnL is amplified using PCR. The PCR product is subsequently sequenced on a next‐generation sequencing platform (Ion Torrent). Amplicon molecules are sequenced individually, allowing identification of different sequences from a mixed sample. We show that this method provides an accurate qualitative and quantitative view of the species composition of samples of airborne pollen grains. We also show that it correctly identifies the individual grass genera present in a mixed sample of grass pollen, which cannot be achieved using microscopic pollen identification. We conclude that our method is more efficient and sensitive than current pollen monitoring techniques and therefore has the potential to increase the throughput of pollen monitoring.     

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.     

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.     

应用DNA复合条形码技术研究秦岭水生动物多样性

基于新一代测序技术的DNA复合条形码技术,以其简便快捷和省时省力的特点,已经成为监测生物多样性的主要方法。采用这一技术,选取COⅠ和18S rRNA两个条形码标记,对秦岭5个淡水水域内,不同生境下10个样品的水生动物多样性进行了初步调查。区系组成结果显示:18S rRNA基因鉴定了9门42纲52目,COⅠ基因鉴定了5门11纲36目,而两个条形码标记共鉴定了10门48纲89目。群落组成分析结果显示:COⅠ分析得到样本中含量相对较高的类群是双翅目、毛翅目、基眼目、鞘翅目、蜉蝣目等;而18S rRNA分析得到样本中主要有节肢动物门、软体动物门和扁形动物门三个大门。此外,两者的分析结果也表明所选样地下游的类群数要高于上游。α多样性分析结果显示:金龙峡、沣峪口和石砭峪3个受人类影响较大样地的群落丰富度和群落多样性相对较高,而五台山和子午峪两个自然样地的物种丰富度和群落多样性相对较低,表明一定程度的外来干扰会对一个地方的水生生物多样性有明显的提高。β多样性分析结果显示,不同环境因素下样品的群落结构差异性较大,而相似环境因素下样品的群落结构差异性则相对较小。此外,在聚类分析时,环境相似性较高的样品首先聚集在一起,而且群落相似性也相对较高。     

A new approach to molecular biosurveillance of invasive species using DNA metabarcoding

Non‐indigenous species (NIS) reach every corner of the world, at times wreaking havoc on ecosystems and costing the global economy billions of dollars. A rapid and accurate biosurveillance tool tailored to a particular biogeographic region is needed to detect NIS when they are first introduced into an area as traditional detection methods are expensive and require specialized expertise. Metabarcoding of environmental and community DNA meets those biosurveillance requirements; a novel tool tailored to the Northwest Pacific Ocean is presented here using an approach that could revolutionize early detection of NIS. Eight newly designed genetic markers for multiple gene regions were implemented to meet the stringent taxonomic requirements for the detection of NIS across four major marine phyla. The tool was considered highly successful because it identified 12 known NIS in the study area and a further seven species representing potential new records. Overall community composition detected here was statistically different between substrate types; zooplankton sampling accounted for significantly higher species richness than filtered sea water in most cases, but this was dominated by mollusk and arthropod species. Both substrate types sampled were required to identify the wide taxonomic breadth of known NIS in the study area. Intensive sampling is known to be paramount for the detection of rare species, including new incursions of NIS, thus it is recommended to include diverse DNA sampling protocols based on species’ life‐history characteristics for broad detection capacity. Application of a metabarcoding‐based molecular biosurveillance tool optimized for biogeographic regions enables rapid and accurate early detection across a wide taxonomic range to allow quick implementation of eradication or control efforts and potentially mitigate some of the devastating effects of NIS worldwide.     

环境DNA metabarcoding及其在生态学研究中的应用

环境DNA metabarcoding(eDNA metabarcoding)是指利用环境样本(如土壤、水、粪便等)中分离的DNA进行高通量的多个物种(或高级分类单元)鉴定的方法。近年来,该方法引起了学者的广泛关注,逐渐应用于生物多样性研究、水生生物监测、珍稀濒危物种和外来入侵物种检测等生态学领域。介绍环境DNA metabarcoding的含义和研究方法;重点介绍环境DNA metabarcoding在物种监测、生物多样性研究和食性分析等生态学领域中的应用;总结环境DNA metabarcoding应用于生态学研究领域面临的挑战并对该方法的发展进行展望。     

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.     

Investigating seed bank potential of crustose coralline algae using DNA metabarcoding

To examine the potential for the autogenic ecosystem engineers, crustose coralline algae (CCA), to serve as seed banks or refugia for life stages of other species, it is critical to develop sampling protocols that reflect the diversity of life present. In this pilot study on two shallow water species of CCA collected from Raoul Island (Kermadec Islands; Rangitāhua) New Zealand, we investigated two preservation methods (ethanol vs. silica gel), sampled inner and outer regions of the crusts, and used DNA metabarcoding and seven genes/gene regions (16S rRNA, 18S rRNA, 23S rRNA, cox1, rbcL, and tufA genes and the ITS rRNA region) to develop a protocol for taxa identification. The results revealed immense diversity, with typically more taxa identified within the inner layers than the outer layers. As highlighted in other metabarcoding studies and in earlier work on rhodoliths (nodose coralline algae), reference databases are incomplete, and to some extent, the use of multiple markers mitigates this issue. Specifically, the 23S rRNA and rbcL genes are currently more suitable for identifying algae, while the cox1 gene fares better at capturing the diversity present inclusive of algae. Further investigation of these autogenic ecosystem engineers that likely act as marine seed banks is needed.     

Reconstructing marine plankton food web interactions using DNA metabarcoding

Knowledge of zooplankton in situ diet is critical for accurate assessment of marine ecosystem function and structure, but due to methodological constraints, there is still a limited understanding of ecological networks in marine ecosystems. Here, we used DNA‐metabarcoding to study trophic interactions, with the aim to unveil the natural diet of zooplankton species under temporal variation of food resources. Several target consumers, including copepods and cladocerans, were investigated by sequencing 16S rRNA and 18S rRNA genes to identify prokaryote and eukaryote potential prey present in their guts. During the spring phytoplankton bloom, we found a dominance of diatom and dinoflagellate trophic links to copepods. During the summer period, zooplankton including cladocerans showed a more diverse diet dominated by cyanobacteria and heterotrophic prey. Our study suggests that copepods present trophic plasticity, changing their natural diet over seasons, and adapting their feeding strategies to the available prey spectrum, with some species being more selective. We did not find a large overlap of prey consumed by copepods and cladocerans, based on prey diversity found in their guts, suggesting that they occupy different roles in the trophic web. This study represents the first molecular approach to investigate several zooplankton–prey associations under seasonal variation, and highlights how, unlike other techniques, the diversity coverage is high when using DNA, allowing the possibility to detect a wide range of trophic interactions in plankton communities.     

Application of plant metabarcoding to identify diverse honeybee pollen forage along an urban–agricultural gradient

Understanding animal foraging ecology requires large sample sizes spanning broad environmental and temporal gradients. For pollinators, this has been hampered by the laborious nature of morphologically identifying pollen. Identifying pollen from urban environments is particularly difficult due to the presence of diverse ornamental species associated with consumer horticulture. Metagenetic pollen analysis represents a potential solution to this issue. Building upon prior laboratory and bioinformatic methods, we applied quantitative multilocus metabarcoding to characterize the foraging ecology of honeybee colonies situated in urban, suburban, mixed suburban–agricultural and rural agricultural sites in central Ohio, USA. In cross‐validating a subset of our metabarcoding results using microscopic palynology, we find strong concordance between the molecular and microscopic methods. Our results suggest that forage from the agricultural site exhibited decreased taxonomic diversity and temporal turnover relative to the urban and suburban sites, though the generalization of this observation will require replication across additional sites and cities. Our work demonstrates the power of honeybees as environmental samplers of floral community composition at large spatial scales, aiding in the distinction of taxa characteristically associated with urban or agricultural land use from those distributed ubiquitously across the sampled landscapes. Observed patterns of high forage diversity and compositional turnover in our more urban sites are likely reflective of the fine‐grain heterogeneity and high beta diversity of urban floral landscapes at the scale of honeybee foraging. This provides guidance for future studies investigating how relationships between urbanization and measures of pollinator health are mediated by variation in floral resource dynamics across landscapes.     

Seasonal and spatial variability of zooplankton diversity in the Poyang Lake Basin using DNA metabarcoding

Freshwater ecosystems face multiple threats to their stability globally. Poyang Lake is the largest lake in China, but its habitat has been seriously degraded because of human activities and natural factors (e.g. climate change), resulting in a decline in freshwater biodiversity. Zooplankton are useful indicators of environmental stressors because they are sensitive to external perturbations. DNA metabarcoding is an approach that has gained significant traction by aiding ecosystem conservation and management. Here, the seasonal and spatial variability in the zooplankton diversity were analyzed in the Poyang Lake Basin using DNA metabarcoding. The results showed that the community structure of zooplankton exhibited significant seasonal and spatial variability using DNA metabarcoding, where the community structure was correlated with turbidity, water temperature, pH, total phosphorus, and chlorophyll‐a. These results indicated habitat variations affected by human activities and seasonal change could be the main driving factors for the variations of zooplankton community. This study also provides an important reference for the management of aquatic ecosystem health and conservation of aquatic biodiversity.