基于环境DNA-宏条形码技术的水生生态系统入侵生物的早期监测与预警

外来生物入侵是继生境破坏后造成生物多样性丧失的第二大威胁因素, 已对入侵地的生态安全、经济和社会发展及人类健康等造成严重负面影响, 成为21世纪五大全球性环境问题之一。作为水产养殖、航运和水生宠物交易大国, 我国水生生态系统的生物入侵问题尤为严重。研究表明, 系统地构建并应用早期监测预警技术是防控水生生态系统生物入侵最有效的途径。和陆生生物相比, 水生生物群落的物种繁多、群落结构复杂、生物形体微小且在入侵初期群体规模极小、隐匿于水下、可用于物种鉴定的外部形态缺乏, 使得在水生生态系统中构建并应用早期监测和预警体系在技术层面更具挑战。随着高通量测序技术的快速发展, 环境DNA-宏条形码技术成为构建水生生态系统入侵生物早期监测与预警技术的首选。本文主要综述了基于环境DNA-宏条形码技术的水生生态系统入侵生物的早期监测与预警技术方法; 解析了环境DNA-宏条形码监测系统的应用现状、技术优势; 着重探讨了影响监测结果准确性的I型和II型错误及其产生原因, 并为避免两类错误提供了可行的优化/改进方案; 最后对该方法在水生入侵生物监测中的应用前景进行了展望。     

基于环境DNA宏条形码技术的秦淮河生物多样性研究

秦淮河是南京的母亲河,其生物多样性受城市化进程影响面临严重威胁,而物种资源调研是生物多样性保护的基础。环境DNA宏条形码技术较形态学监测是一种简单高效、灵敏度高的新型监测技术。为探究秦淮河浮游生物、底栖动物及鱼类的生物多样性,于2019年7月,采用环境DNA宏条形码技术对其进行了探究,并分析了秦淮河上下游间的差异及环境因子对其群落结构的影响。结果表明:秦淮河共监测到浮游动物13属22种407个操作分类单元(Operational Taxonomic Units, OTUs),浮游植物85属60种4445个OTUs,底栖动物16属17种212个OTUs,鱼类53属44种1663个OTUs。其中浮游动物以游泳轮虫目(Ploima)和双甲目(Diplostraca)为主,共占浮游动物63.37%,浮游植物以隐藻门(Cryptomonas)和褐藻门(Ochrophyta)为主,共占浮游植物88.11%,底栖动物中节肢动物门(Arthropoda)占比最高,达91.67%,鱼类中鲤形目(Cypriniformes)占比最高,达69.99%。与秦淮河历史形态学监测数据相比,环境DNA宏条形码技术在...     

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。     

DNA宏条形码技术在海洋浮游动物多样性和生态学研究中的应用

浮游动物是海洋生态系统的关键类群,其覆盖门类广泛,多样性高。传统形态鉴定技术需要检测人员具备专业的形态鉴定知识,且费时费力。宏条形码技术无需分离生物个体,而是提取拖网采集到的浮游动物混合样本的总DNA,或者水体中的环境DNA （eDNA）,依托高通量测序平台测序,能够实现对大规模样本快速、准确、经济的分析,在海洋浮游动物生态学研究中得到越来越广泛的应用。分析了DNA宏条形码技术常用的核糖体和线粒体分子标记,在浮游动物多样性和数量研究中的可靠性和不足,并给出在海洋浮游动物群落监测,食物关系分析及生物入侵早期预警等研究中的应用。未来,开发多基因片段组合条形码,发展完备的参考数据库及实现准确的量化研究是DNA宏条形码技术发展的重要方向。     

DNA宏条形码技术在食草动物食性研究中的应用

随着测序技术的快速发展,整合DNA条形码和高通量测序的DNA宏条形码技术已经成为当前研究热点之一,在食草动物的食性鉴定中有很大潜力。放牧动物食性研究是动物营养学和草地生态学领域的重要研究内容。而与传统食性研究方法相比,宏条形码技术可通过对植物DNA条形码的高通量测序,获得样本中的物种组成进而分析动物食性。介绍了传统食性分析手段的局限,重点综述了DNA宏条形码技术的产生、操作原理以及在食草类动物食性鉴定领域中的应用,同时还简述了可能存在的挑战,并对该技术今后的发展方向进行了展望。     

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。     

基于环境DNA宏条形码技术的辽东湾典型围海养殖池塘内水母多样性研究

研究使用环境DNA宏条形码技术(eDNA metabarcoding)检测辽东湾东北部河口区围海养殖池塘水母种类多样性,探索适用于水母种类物种鉴定和监测的新方法。利用环境DNA宏条形码技术,分别基于18S rDNA和COI宏条形码检测了辽东湾东北部河口区围海养殖池塘水母种类多样性,通过水样采集、过滤、eDNA提取、遗传标记扩增、测序与生物信息分析的环境DNA宏条形码标准化分析流程,从围海养殖池塘7个采样点中获得可检测的采样点数据。结果显示,基于18S rDNA宏条形码检测出8种水母种类,其中钵水母纲大型水母2种、水螅水母总纲小型水母6种;基于COI宏条形码技术共检测出19种水母种类,其中钵水母纲大型水母5种、水螅水母总纲小型水母14种;两种DNA条形码标记都显示养殖种类海蜇(Rhopilema esculentum)为优势种。研究结果表明,环境DNA宏条形码技术作为一种新兴的生物多样性监测手段可用于快速检测水母种类多样性,在水母类物种鉴定、监测及早期预警中有较大的应用潜能。     

环境DNA技术在淡水底栖大型无脊椎动物多样性监测中的应用

环境DNA (eDNA)是指生物有机体在环境中(例如土壤、沉积物或水体)遗留下的DNA片段。eDNA技术是指从环境中提取DNA片段进行测序以及数据分析来反映环境中的物种或群落信息。与传统方法相比, eDNA技术具有高灵敏度、省时省力、无损伤等优点。目前, eDNA技术已成为一种新的水生生物监测方法, 主要应用于水生生物的多样性研究、濒危和稀有动物的物种状态及外来入侵动物扩散动态的监测等。本文从eDNA技术在水生生物多样性监测应用领域的发展历程、eDNA技术的操作流程以及其在监测淡水底栖大型无脊椎动物方面的应用进展、技术优势和局限性五个方面进行了综述。最后, 本文对eDNA技术在淡水底栖大型无脊椎动物多样性监测应用的发展趋势和前景作出展望。     

不同环境样本类型对蚌类环境DNA监测的差异研究

为了阐明在使用环境DNA宏条形码技术时不同环境样本类型如何影响蚌类物种的可检测性,于2021年冬季和春季在鄱阳湖分别采集表层水、底层水和沉积物进行环境DNA宏条形码分析,并结合传统方法采集验证。基于环境DNA宏条形码技术共检测到鄱阳湖蚌类33种,传统方法共采集蚌类18种,环境DNA宏条形码技术能检测出传统方法采集到的所有蚌类物种。表层水和底层水注释到的蚌类物种数均分别高于沉积物的,且表层水和底层水注释到的蚌类物种分别完全覆盖沉积物的。基于环境DNA宏条形码技术的蚌类α多样性水平季节差异不显著,但蚌类β多样性水平季节差异显著。表层水和底层水的蚌类多样性均显著高于沉积物样本的, Beta多样性分析也显示水体样本(表层水和底层水分别)和沉积物样本存在显著性差异。但表层水和底层水的蚌类多样性和群落结构均无显著差异。鄱阳湖蚌类群落结构与环境因子的关联分析表明水深(WD)、透明度(SD)、水温(WT)和总氮(TN)显著影响蚌类群落结构。环境DNA宏条形码技术在蚌类的多样性监测中可行,且采水样比采沉积物效果好,表层水和底层水无显著差异。     

动物食性分析在生态学中的应用研究进展——基于DNA宏条形码技术

动物食性分析是动物营养生态学的重要研究手段,可用于解析动物与环境因素的关联性、捕食者与猎物之间的关系,以及动物物种多样性等科学问题。近年来,基于新一代测序技术的DNA宏条形码技术被广泛应用到生态学多个研究领域,极大地促进了生命科学交叉学科的发展。其中,DNA宏条形码技术在动物食性分析中具有高分辨、高效率、低样本量等优势,具有重要的应用前景。综述了基于DNA宏条形码技术的动物食性分析在生态学中的应用研究进展,并进一步总结了DNA宏条形码技术原理和食性分析方法,着重探讨了基于DNA宏条形码技术的动物食性分析在珍稀濒危动物保护、生物多样性监测、农业害虫防治等生态学研究领域中的应用,并对DNA宏条形码技术在动物食性分析中存在的问题及应用前景进行小结与展望。     

Environmental DNA metabarcoding: Transforming how we survey animal and plant communities

The genomic revolution has fundamentally changed how we survey biodiversity on earth. High‐throughput sequencing (“HTS”) platforms now enable the rapid sequencing of DNA from diverse kinds of environmental samples (termed “environmental DNA” or “eDNA”). Coupling HTS with our ability to associate sequences from eDNA with a taxonomic name is called “eDNA metabarcoding” and offers a powerful molecular tool capable of noninvasively surveying species richness from many ecosystems. Here, we review the use of eDNA metabarcoding for surveying animal and plant richness, and the challenges in using eDNA approaches to estimate relative abundance. We highlight eDNA applications in freshwater, marine and terrestrial environments, and in this broad context, we distill what is known about the ability of different eDNA sample types to approximate richness in space and across time. We provide guiding questions for study design and discuss the eDNA metabarcoding workflow with a focus on primers and library preparation methods. We additionally discuss important criteria for consideration of bioinformatic filtering of data sets, with recommendations for increasing transparency. Finally, looking to the future, we discuss emerging applications of eDNA metabarcoding in ecology, conservation, invasion biology, biomonitoring, and how eDNA metabarcoding can empower citizen science and biodiversity education.     

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

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

Scaling up DNA metabarcoding for freshwater macrozoobenthos monitoring

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eDNA metabarcoding survey reveals fine‐scale coral reef community variation across a remote,tropical island ecosystem

Environmental DNA (eDNA) metabarcoding, a technique for retrieving multispecies DNA from environmental samples, can detect a diverse array of marine species from filtered seawater samples. There is a growing potential to integrate eDNA alongside existing monitoring methods in order to establish or improve the assessment of species diversity. Remote island reefs are increasingly vulnerable to climate‐related threats and as such there is a pressing need for cost‐effective whole‐ecosystem surveying to baseline biodiversity, study assemblage changes and ultimately develop sustainable management plans. We investigated the utility of eDNA metabarcoding as a high‐resolution, multitrophic biomonitoring tool at the Cocos (Keeling) Islands, Australia (CKI)—a remote tropical coral reef atoll situated within the eastern Indian Ocean. Metabarcoding assays targeting the mitochondrial 16S rRNA and CO1 genes, as well as the 18S rRNA nuclear gene, were applied to 252 surface seawater samples collected from 42 sites within a 140 km² area. Our assays successfully detected a wide range of bony fish and elasmobranchs (244 taxa), crustaceans (88), molluscs (37) and echinoderms (7). Assemblage composition varied significantly between sites, reflecting habitat partitioning across the island ecosystem and demonstrating the localisation of eDNA signals, despite extensive tidal and oceanic movements. In addition, we document putative new occurrence records for 46 taxa and compare the efficiency of our eDNA approach to visual survey techniques at CKI. Our study demonstrates the utility of a multimarker metabarcoding approach in capturing multitrophic biodiversity across an entire coral reef atoll and sets an important baseline for ongoing monitoring and management.     

Needle in a haystack? A comparison of eDNA metabarcoding and targeted qPCR for detection of the great crested newt (Triturus cristatus)

Environmental DNA (eDNA) analysis is a rapid, cost‐effective, non‐invasive biodiversity monitoring tool which utilises DNA left behind in the environment by organisms for species detection. The method is used as a species‐specific survey tool for rare or invasive species across a broad range of ecosystems. Recently, eDNA and “metabarcoding” have been combined to describe whole communities rather than focusing on single target species. However, whether metabarcoding is as sensitive as targeted approaches for rare species detection remains to be evaluated. The great crested newt Triturus cristatus is a flagship pond species of international conservation concern and the first UK species to be routinely monitored using eDNA. We evaluate whether eDNA metabarcoding has comparable sensitivity to targeted real‐time quantitative PCR (qPCR) for T. cristatus detection. Extracted eDNA samples (N = 532) were screened for T. cristatus by qPCR and analysed for all vertebrate species using high‐throughput sequencing technology. With qPCR and a detection threshold of 1 of 12 positive qPCR replicates, newts were detected in 50% of ponds. Detection decreased to 32% when the threshold was increased to 4 of 12 positive qPCR replicates. With metabarcoding, newts were detected in 34% of ponds without a detection threshold, and in 28% of ponds when a threshold (0.028%) was applied. Therefore, qPCR provided greater detection than metabarcoding but metabarcoding detection with no threshold was equivalent to qPCR with a stringent detection threshold. The proportion of T. cristatus sequences in each sample was positively associated with the number of positive qPCR replicates (qPCR score) suggesting eDNA metabarcoding may be indicative of eDNA concentration. eDNA metabarcoding holds enormous potential for holistic biodiversity assessment and routine freshwater monitoring. We advocate this community approach to freshwater monitoring to guide management and conservation, whereby entire communities can be initially surveyed to best inform use of funding and time for species‐specific surveys.     

eDNA metabarcoding as a new surveillance approach for coastal Arctic biodiversity

Because significant global changes are currently underway in the Arctic, creating a large‐scale standardized database for Arctic marine biodiversity is particularly pressing. This study evaluates the potential of aquatic environmental DNA (eDNA) metabarcoding to detect Arctic coastal biodiversity changes and characterizes the local spatio‐temporal distribution of eDNA in two locations. We extracted and amplified eDNA using two COI primer pairs from ~80 water samples that were collected across two Canadian Arctic ports, Churchill and Iqaluit, based on optimized sampling and preservation methods for remote regions surveys. Results demonstrate that aquatic eDNA surveys have the potential to document large‐scale Arctic biodiversity change by providing a rapid overview of coastal metazoan biodiversity, detecting nonindigenous species, and allowing sampling in both open water and under the ice cover by local northern‐based communities. We show that DNA sequences of ~50% of known Canadian Arctic species and potential invaders are currently present in public databases. A similar proportion of operational taxonomic units was identified at the species level with eDNA metabarcoding, for a total of 181 species identified at both sites. Despite the cold and well‐mixed coastal environment, species composition was vertically heterogeneous, in part due to river inflow in the estuarine ecosystem, and differed between the water column and tide pools. Thus, COI‐based eDNA metabarcoding may quickly improve large‐scale Arctic biomonitoring using eDNA, but we caution that aquatic eDNA sampling needs to be standardized over space and time to accurately evaluate community structure changes.     

Environmental DNA (eDNA) metabarcoding reveals strong discrimination among diverse marine habitats connected by water movement

While in recent years environmental DNA (eDNA) metabarcoding surveys have shown great promise as an alternative monitoring method, the integration into existing marine monitoring programs may be confounded by the dispersal of the eDNA signal. Currents and tidal influences could transport eDNA over great distances, inducing false‐positive species detection, leading to inaccurate biodiversity assessments and, ultimately, mismanagement of marine environments. In this study, we determined the ability of eDNA metabarcoding surveys to distinguish localized signals obtained from four marine habitats within a small spatial scale (<5 km) subject to significant tidal and along‐shore water flow. Our eDNA metabarcoding survey detected 86 genera, within 77 families and across 11 phyla using three established metabarcoding assays targeting fish (16S rRNA gene), crustacean (16S rRNA gene) and eukaryotic (cytochrome oxidase subunit 1) diversity. Ordination and cluster analyses for both taxonomic and OTU data sets show distinct eDNA signals between the sampled habitats, suggesting dispersal of eDNA among habitats was limited. Individual taxa with strong habitat preferences displayed localized eDNA signals in accordance with their respective habitat, whereas taxa known to be less habitat‐specific generated more ubiquitous signals. Our data add to evidence that eDNA metabarcoding surveys in marine environments detect a broad range of taxa that are spatially discrete. Our work also highlights that refinement of assay choice is essential to realize the full potential of eDNA metabarcoding surveys in marine biodiversity monitoring programs.     

Next‐generation monitoring of aquatic biodiversity using environmental DNA metabarcoding

Global biodiversity in freshwater and the oceans is declining at high rates. Reliable tools for assessing and monitoring aquatic biodiversity, especially for rare and secretive species, are important for efficient and timely management. Recent advances in DNA sequencing have provided a new tool for species detection from DNA present in the environment. In this study, we tested whether an environmental DNA (eDNA) metabarcoding approach, using water samples, can be used for addressing significant questions in ecology and conservation. Two key aquatic vertebrate groups were targeted: amphibians and bony fish. The reliability of this method was cautiously validated in silico, in vitro and in situ. When compared with traditional surveys or historical data, eDNA metabarcoding showed a much better detection probability overall. For amphibians, the detection probability with eDNA metabarcoding was 0.97 (CI = 0.90–0.99) vs. 0.58 (CI = 0.50–0.63) for traditional surveys. For fish, in 89% of the studied sites, the number of taxa detected using the eDNA metabarcoding approach was higher or identical to the number detected using traditional methods. We argue that the proposed DNA‐based approach has the potential to become the next‐generation tool for ecological studies and standardized biodiversity monitoring in a wide range of aquatic ecosystems.