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...     

基于环境DNA宏条形码的洱海鱼类多样性研究

研究使用环境DNA宏条形码(eDNA metabarcoding)检测洱海鱼类多样性,探索适用于洱海鱼类多样性监测和保护的新方法。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,从洱海16个采样点中获得可检测的9个采样点数据,共检测出17种鱼类,其中土著种5种、外来种12种;鲫(Carassius auratus)、鳙(Hypophthalmichthys nobilis)、麦穗鱼(Pseudorasbora parva)、泥鳅(Misgurnus anguillicaudatus)和食蚊鱼(Gambusia affinis)为优势种。研究结果表明虽然环境DNA宏条形码无法完全替代传统的鱼类监测方法,但作为一种新兴的生物多样性监测手段,其可用于快速检测洱海鱼类多样性及其空间分布。     

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。     

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。     

环境DNA宏条形码在生物多样性研究与监测中的应用

环境DNA宏条形码(eDNA metabarcoding)技术通过提取水体、土壤、空气中的环境DNA,使用引物PCR扩增与高通量测序,进行物种鉴定与生物多样性评估.作为一种新的监测技术,相比于传统监测技术更加快捷、准确以及对自然环境的破坏小,因此在一定程度上改变了我们调查地球生物多样性的方式.本文综述了环境DNA宏条形...     

基于主成分分析的音乐事件相关脑电变化研究

目的:对在不同音乐背景下获取的脑电数据进行主成分分析.方法:在受测者闭眼欣赏喜欢音乐,闭眼欣赏不喜欢音乐,安静闭眼期间获得脑电数据,并对其进行主成分分析,提取第一主成分,主成分荷载,得出在不同条件和不同事件下主成分的变化规律以及影响主成分变化脑电极的变化规律.数据处理和统计分析采用独立设计的脑电图分析工具箱和主成分分析程序.结果:脑电图数据经过主成分分析后,第一主成分贡献率变化就有比较明显的规律,在闭眼欣赏喜欢音乐时,第一主成分贡献率明显比欣赏不喜欢音乐和安静闭眼时高.在前头部,欣赏喜欢音乐时和欣赏不喜欢音乐时,影响第一主成分的脑电极分别在右前头部和左前头部脑电信号比较强.结论:在不同音乐背景下,大脑左右前头部会受不同音乐所影响,同时也会对人的感觉,情感,情绪等会产生重要的影响.     

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。     

基于粪便DNA及宏条形码技术的食肉动物快速调查及食性分析

在陆地生态系统中, 大型食肉动物对于稳定食物网结构和生态系统功能有重要作用。在世界范围内, 由于栖息地丧失和破碎化、猎杀、人类活动干扰以及病原体的传播, 大型食肉动物生存正面临严重威胁, 多种食肉动物地理分布范围及种群数量大幅度缩减。如何有效保护大型食肉动物物种多样性及种群已经成为世界关注的焦点问题和保护生物学的重要研究方向。川西高原地处我国西南山地与青藏高原东缘交界地带, 属于世界生物多样性热点地区, 是世界大型食肉动物物种最丰富的地区之一, 而日益增强的人类活动可能会加剧对当地动植物资源的破坏, 进而威胁野生食肉动物的生存。获得准确的物种多样性信息及食肉动物食性数据有助于深入了解该地区生态系统结构及食物网关系, 对研究物种共存机制及生物多样性保护有重要意义。本研究通过从四川甘孜藏族自治州新龙县和石渠县野外采集的食肉动物粪便样品中提取DNA, 利用DNA条形码进行物种鉴定, 快速获得该地区食肉动物物种构成信息。38份粪便样品经鉴定来自于7种食肉动物, 分别为5种大型食肉动物(狼Canis lupus、棕熊Ursus arctos、豹Panthera pardus、雪豹P. unica、狗Canis lupus familiaris)和2种中小型食肉动物(豹猫Prionailurus bengalensis、赤狐Vulpes vulpes)。进一步利用高通量测序和宏条形码技术对7种食肉动物粪便中的食物DNA进行精准食性分析, 得到包含19种哺乳类、8种鸟类和1种鱼类共计28个不同的食物分子可操作分类单元(molecular operational taxonomic unit, MOTU)。结果显示, 狼、狗、棕熊最主要的食物来源为偶蹄目动物, 其中取食频率最高的物种为家牦牛(Bos grunniens); 而豹猫和赤狐食物中小型哺乳动物如啮齿目和兔形目占重要比例, 其中高原松田鼠(Neodon irene)和高原鼠兔(Ochotona curzoniae)被取食频率最高。豹和雪豹的食物分别为偶蹄目的中华斑羚(Naemorhedus griseus)和岩羊(Pseudois nayaur)。本研究显示了粪便DNA及宏条形码技术在食肉动物多样性快速调查及高通量精确食性分析中的应用前景, 并为此类研究提供了技术路线的有力借鉴。     

基于环境DNA宏条形码技术的北京地区鱼类多样性调查和外来鱼种入侵风险评估

[目的]调查北京地区鱼类多样性和群落分布及评估外来鱼种的入侵风险.[方法]选取北京地区水库、湖泊和河流3种水体类型共33个采样点,于2020年6月10—17日开展水生态监测,利用环境DNA宏条形码技术对各样点的鱼类多样性和群落结构进行监测和分析,对目前北京地区水生态系统中本地鱼种和外来鱼种进行分类汇总,并评估典型外来入...     

基于环境DNA宏条形码技术研究黄河三角洲典型潮沟系统鱼类多样性及其对水文连通性的响应

水文连通对于维护滨海湿地生物多样性至关重要,鱼类多样性作为生物多样性的重要组成部分,了解其对不同水文连通强度的响应具有重要意义。本研究基于环境DNA宏条形码技术(e DNA metabarcoding)检测黄河三角洲典型潮沟系统鱼类多样性,分析鱼类物种分布对不同水文连通强度潮沟生境差异的响应特征。利用12S r RNA经典鱼类引物对采集自三级潮沟系统的水样进行高通量测序,共检测出鱼类55种,其中本地鱼类27种、非本地鱼类28种,物种组成以鲈形目为主。各样点序列丰度均较高的鱼类有矛尾刺虾虎鱼(Acanthogobius hasta)、鮻(Planiliza haematocheilus)、长体刺虾虎鱼(Acanthogobius elongatus)等。鱼类多样性在不同水文连通性潮沟间差异明显,其中,二级潮沟群落多样性水平、丰富度指数、物种种类及各种鱼类类群中的个体均匀程度等都明显高于其他两级潮沟。RDA分析显示有6种环境因子与鱼类群落结构显著相关(P<0.05),分别为:硅酸盐(Si O₃^2––Si)、硝酸盐(NO₃     

Meta-Fish-Lib: A generalised,dynamic DNA reference library pipeline for metabarcoding of fishes

The accuracy and reliability of DNA metabarcoding analyses depend on the breadth and quality of the reference libraries that underpin them. However, there are limited options available to obtain and curate the huge volumes of sequence data that are available on public repositories such as NCBI and BOLD. Here, we provide a pipeline to download, clean and annotate mitochondrial DNA sequence data for a given list of fish species. Features of this pipeline include (a) support for multiple metabarcode markers; (b) searches on species synonyms and taxonomic name validation; (c) phylogeny assisted quality control for identification and removal of misannotated sequences; (d) automatically generated coverage reports for each new GenBank release update; and (e) citable, versioned DOIs. As an example we provide a ready-to-use curated reference library for the marine and freshwater fishes of the U.K. To augment this reference library for environmental DNA metabarcoding specifically, we generated 241 new MiFish-12S sequences for 88 U.K. marine species, and make available new primer sets useful for sequencing these. This brings the coverage of common U.K. species for the MiFish-12S fragment to 93%, opening new avenues for scaling up fish metabarcoding across wide spatial gradients. The Meta-Fish-Lib reference library and pipeline is hosted at https://github.com/genner-lab/meta-fish-lib .     

Bioinformatics matters: The accuracy of plant and soil fungal community data is highly dependent on the metabarcoding pipeline

Fungal communities associated with plants and soil influence plant fitness and ecosystem functioning. They are frequently studied by metabarcoding approaches targeting the ribosomal internal transcribed spacer (ITS), but there is no consensus concerning the most appropriate bioinformatic approach for the analysis of these data. We sequenced an artificial fungal community composed of 189 strains covering a wide range of Ascomycota and Basidiomycota, to compare the performance of 360 software and parameter combinations. The most sensitive approaches, based on the USEARCH and VSEARCH clustering algorithms, detected almost all fungal strains but greatly overestimated the total number of strains. By contrast, approaches using DADA2 to detect amplicon sequence variants were the most effective for recovering the richness and composition of the fungal community. Our results suggest that analyzing single forward (R1) sequences with DADA2 and no filter other than the removal of low-quality and chimeric sequences is a good option for fungal community characterization.     

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.     

DNA metabarcoding unveils multiscale trophic variation in a widespread coastal opportunist

A thorough understanding of ecological networks relies on comprehensive information on trophic relationships among species. Since unpicking the diet of many organisms is unattainable using traditional morphology‐based approaches, the application of high‐throughput sequencing methods represents a rapid and powerful way forward. Here, we assessed the application of DNA metabarcoding with nearly universal primers for the mitochondrial marker cytochrome c oxidase I in defining the trophic ecology of adult brown shrimp, Crangon crangon, in six European estuaries. The exact trophic role of this abundant and widespread coastal benthic species is somewhat controversial, while information on geographical variation remains scant. Results revealed a highly opportunistic behaviour. Shrimp stomach contents contained hundreds of taxa (>1,000 molecular operational taxonomic units), of which 291 were identified as distinct species, belonging to 35 phyla. Only twenty ascertained species had a mean relative abundance of more than 0.5%. Predominant species included other abundant coastal and estuarine taxa, including the shore crab Carcinus maenas and the amphipod Corophium volutator. Jacobs’ selectivity index estimates based on DNA extracted from both shrimp stomachs and sediment samples were used to assess the shrimp's trophic niche indicating a generalist diet, dominated by crustaceans, polychaetes and fish. Spatial variation in diet composition, at regional and local scales, confirmed the highly flexible nature of this trophic opportunist. Furthermore, the detection of a prevalent, possibly endoparasitic fungus (Purpureocillium lilacinum) in the shrimp's stomach demonstrates the wide range of questions that can be addressed using metabarcoding, towards a more robust reconstruction of ecological networks.     

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.     

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。     

Measuring global fish species richness with eDNA metabarcoding

Despite mounting threats to global freshwater and marine biodiversity, including climate change, habitat alteration, overharvesting and pollution, we struggle to know which species are present below the water's surface that are suffering from these stressors. However, the idea that a water sample containing environmental DNA (eDNA) can be screened using high‐throughput sequencing and bioinformatics to reveal the identity of aquatic species is a revolutionary advance for studying the patterns of species extirpation, invasive species establishment and the dynamics of species richness. To date, many of the critical tests of fisheries diversity using this metabarcoding approach have been conducted in lower diversity systems (<40 fish species), but in this issue of Molecular Ecology Resources, Cilleros et al. (2018) described their eDNA application in the species‐rich French Guiana fishery (>200 fish species) and showed the greater potential and some limitations of using eDNA in species‐rich environments.     

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.     

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.