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 .     

DNA条形码参考数据集构建和序列分析相关的新兴技术

近年来DNA条形码技术迅速发展, 产生的条形码的数量及其应用范围都呈指数性增长, 现已广泛用于物种鉴定、食性分析、生物多样性评估等方面。本文重点总结并讨论了构建条形码参考数据库和序列聚类相关的信息分析的技术和方法, 包括: 基于高通量测序(high throughput sequencing, HTS)平台以高效并较低的成本获取条形码序列的方法; 同时还介绍了从原始测序序列到分类操作单元(operational taxonomic units, OTUs)过程中的一些计算逻辑以及被广泛采用的软件和技术。这是一个较新并快速发展的领域, 我们希望本文能为读者提供一个梗概, 了解DNA条形码技术在生物多样性研究应用中的方法和手段。     

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 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 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.     

Evaluation of the DNA barcoding approach to develop a reference data-set for the threatened flora of Sicily

The Mediterranean Basin is one of the most significantly altered World Biodiversity Hotspots with extensive habitat loss and fast genetic population erosion, for which urgent biodiversity reconnaissance and preservation actions are required. In particular, Sicily has about 600 taxa classified as threatened or near-threatened. The correct recognition and identification of such biodiversity is required for supporting further activities. The objective of this work is to assess the ability of the DNA barcoding approach to identify different taxonomic groups from a collection of the most threatened plant taxa, throughout natural Sicilian populations. The evaluation of the DNA barcoding core markers, rbcL and matK, was carried out on 30 taxa belonging to 13 families. DNA barcode fragments were recovered from all taxa (100%). The rbcL gene was recovered from 97% of the taxa and matK gene from 73%. In this test, 19 taxa overall (63%) were totally resolved at the specific or subspecific level, by at least one of the core markers. Fourteen of the 17 most threatened taxa (EN, CR) included in this work were totally discriminated. The matK and rbcL locus, respectively, resolved 64% and 48% of the taxa successfully sequenced. The matK gene expressed the highest genetic distance (K2P value), from 0.4% to 8.6%, against a range of 0.1–2% of rbcL gene. However, the rbcL gene appeared a good compromise between PCR, sequencing success and species-level resolution. Cryptic groups suggest the implementation of additional barcoding markers or different primer combinations, particularly for matK, in order to increase the performances. However, this preliminary result confirms the potential of the barcoding approach for quick identification of unknown and heterogeneous plant groups to generate a dedicated reference data-set of the threatened Sicilian flora for a wide range of applications.     

FuzzyID2: A software package for large data set species identification via barcoding and metabarcoding using hidden Markov models and fuzzy set methods

Species identification through DNA barcoding or metabarcoding has become a key approach for biodiversity evaluation and ecological studies. However, the rapid accumulation of barcoding data has created some difficulties: for instance, global enquiries to a large reference library can take a very long time. We here devise a two‐step searching strategy to speed identification procedures of such queries. This firstly uses a Hidden Markov Model (HMM) algorithm to narrow the searching scope to genus level and then determines the corresponding species using minimum genetic distance. Moreover, using a fuzzy membership function, our approach also estimates the credibility of assignment results for each query. To perform this task, we developed a new software pipeline, FuzzyID2, using Python and C++. Performance of the new method was assessed using eight empirical data sets ranging from 70 to 234,535 barcodes. Five data sets (four animal, one plant) deployed the conventional barcode approach, one used metabarcodes, and two were eDNA‐based. The results showed mean accuracies of generic and species identification of 98.60% (with a minimum of 95.00% and a maximum of 100.00%) and 94.17% (with a range of 84.40%–100.00%), respectively. Tests with simulated NGS sequences based on realistic eDNA and metabarcode data demonstrated that FuzzyID2 achieved a significantly higher identification success rate than the commonly used Blast method, and the TIPP method tends to find many fewer species than either FuzztID2 or Blast. Furthermore, data sets with tens of thousands of barcodes need only a few seconds for each query assignment using FuzzyID2. Our approach provides an efficient and accurate species identification protocol for biodiversity‐related projects with large DNA sequence data sets.     

检疫性疫霉DNA条形码标准分子构建

质粒标准分子是指含有外源基因和内源标准基因特异性片段的重组质粒分子.DNA条形码技术是通过对标准目的基因的DNA序列进行分析从而进行物种鉴定的技术.构建基于DNA条形码的质粒标准分子是DNA条形码技术应用于检测实践的要求.本研究将这两种检测鉴定技术相结合应用于检疫性疫霉的检测,构建了11种检疫性疫霉的DNA条形码标准分子,进行了测序验证,均匀性,稳定性和特异性验证.结果表明,构建的质粒标准分子准确度,均匀性,稳定性和特异性均良好,对实际口岸检验检疫工作具有实践应用价值.     

Spider: an R package for the analysis of species identity and evolution, with particular reference to DNA barcoding

Spider: SPecies IDentity and Evolution in R is a new R package implementing a number of useful analyses for DNA barcoding studies and associated research into species delimitation and speciation. Included are functions essential for generating important summary statistics from DNA barcode data, assessing specimen identification efficacy, and for testing and optimizing divergence threshold limits. In terms of investigating evolutionary and taxonomic questions, techniques for assessing diagnostic nucleotides and probability of reciprocal monophyly are also provided. Additionally, a sliding window function offers opportunities to analyse information across a gene, essential for marker design in degraded DNA studies. Spider capitalizes on R's extensible ethos and offers an integrated platform ideal for the analysis of both nucleotide and morphological data. The program can be obtained from the comprehensive R archive network (CRAN, http://cran.r-project.org) and from the R-Forge package development site (http://spider.r-forge.r-project.org/).     

基于环境DNA-宏条形码技术的底栖动物监测及水质评价研究进展

底栖动物是淡水生态系统中物种多样性最高的类群,也是应用最广泛的水质监测指示生物之一。传统的底栖动物监测以形态学为基础,耗时费力,无法满足流域尺度大规模监测的需求。环境DNA-宏条形码技术是一种新兴的生物监测方法,其与传统方法相比优势在于采样方法简单、低成本、高灵敏度,不受生物样本和环境状况的影响,不依赖分类专家和鉴定资料,能够快速准确地对多个类群进行大规模、高通量的物种鉴定。然而,在实际应用中该方法的效果受诸多因素的影响,不同的方法、流程往往会产生差异较大的结果。鉴于此,着重分析总结了应用环境DNA-宏条形码技术监测底栖动物的关键影响因素,包括样品采集与处理流程、分子标记选择、引物设计、PCR偏好性、参考数据库的完整性及相应的优化。并基于此探讨了提高环境DNA-宏条形码技术在底栖动物监测效率和准确率的途径,以期为底栖动物环境DNA-宏条形码监测方案的制定提供可靠的参考。最后对该技术在底栖动物监测和水质评价中的最新发展方向进行了展望。     

Metabarcoding技术在真菌多样性研究中的应用

由于受到气候变化、土地利用变化及环境污染等诸多因素的干扰, 真菌多样性受到不容忽视的威胁, 亟需得到保护。构建物种数据库是实现真菌多样性研究和保护的重要前提。近年来兴起的DNA条形码及metabarcoding技术能够在很大程度上弥补传统鉴定方法的缺陷, 可对真菌物种进行大规模、准确、快速、高效地鉴定。本文梳理了metabarcoding技术在真菌物种多样性评估、真菌多样性影响机制和真菌古生态重建等研究中的应用, 同时强调了metabarcoding技术用于真菌多样性研究尚处于初期阶段, 在构建有效参照数据库、优化实验流程以及升级生物信息学工具等方面仍需要进一步的完善。建议加强真菌分类学家、生态学家以及计算机工具研发工程师之间的合作, 共同解决metabarcoding技术在真菌多样性研究及应用中面临的问题, 为宏观尺度上真菌多样性保护提供更加科学的依据。     

DNA barcoding of Chinese snakes reveals hidden diversity and conservation needs

DNA barcoding has greatly facilitated studies of taxonomy, biodiversity, biological conservation, and ecology. Here, we establish a reliable DNA barcoding library for Chinese snakes, unveiling hidden diversity with implications for taxonomy, and provide a standardized tool for conservation management. Our comprehensive study includes 1638 cytochrome c oxidase subunit I (COI) sequences from Chinese snakes that correspond to 17 families, 65 genera, 228 named species (80.6% of named species) and 36 candidate species. A barcode gap analysis reveals gaps, where all nearest neighbour distances exceed maximum intraspecific distances, in 217 named species and all candidate species. Three species-delimitation methods (ABGD, sGMYC, and sPTP) recover 320 operational taxonomic units (OTUs), of which 192 OTUs correspond to named and candidate species. Twenty-eight other named species share OTUs, such as Azemiops feae and A. kharini, Gloydius halys, G. shedaoensis, and G. intermedius, and Bungarus multicinctus and B. candidus, representing inconsistencies most probably caused by imperfect taxonomy, recent and rapid speciation, weak taxonomic signal, introgressive hybridization, and/or inadequate phylogenetic signal. In contrast, 43 species and candidate species assign to two or more OTUs due to having large intraspecific distances. If most OTUs detected in this study reflect valid species, including the 36 candidate species, then 30% more species would exist than are currently recognized. Several OTU divergences associate with known biogeographic barriers, such as the Taiwan Strait. In addition to facilitating future studies, this reliable and relatively comprehensive reference database will play an important role in the future monitoring, conservation, and management of Chinese snakes.     

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.     

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.     

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

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

DNA barcoding of Canada's skates

DNA-based identifications have been employed across broad taxonomic ranges and provide an especially useful tool in cases where external identification may be problematic. This study explored the utility of DNA barcoding in resolving skate species found in Atlantic Canadian waters. Most species were clearly resolved, expanding the utility for such identification on a taxonomically problematic group. Notably, one genus (Amblyraja) contained three of four species whose distributions do not overlap that could not be readily identified with this method. On the other hand, two common and partially sympatric species (Little and Winter skates) were readily identifiable. There were several instances of inconsistency between the voucher identification and the DNA sequence data. In some cases, these were at the intrageneric level among species acknowledged to be prone to misidentification. However, several instances of intergeneric discrepancies were also identified, suggesting either evidence of past introgressive hybridization or misidentification of vouchered specimens across broader taxonomic ranges. Such occurrences highlight the importance of retaining vouchered specimens for subsequent re-examination in the light of conflicting DNA evidence.     

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。