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Six DNA regions were evaluated as potential DNA barcodes for Fungi, the second largest kingdom of eukaryotic life, by a multinational, multilaboratory consortium. The region of the mitochondrial cytochrome c oxidase subunit 1 used as the animal barcode was excluded as a potential marker, because it is difficult to amplify in fungi, often includes large introns, and can be insufficiently variable. Three subunits from the nuclear ribosomal RNA cistron were compared together with regions of three representative protein-coding genes (largest subunit of RNA polymerase II, second largest subunit of RNA polymerase II, and minichromosome maintenance protein). Although the protein-coding gene regions often had a higher percent of correct identification compared with ribosomal markers, low PCR amplification and sequencing success eliminated them as candidates for a universal fungal barcode. Among the regions of the ribosomal cistron, the internal transcribed spacer (ITS) region has the highest probability of successful identification for the broadest range of fungi, with the most clearly defined barcode gap between inter- and intraspecific variation. The nuclear ribosomal large subunit, a popular phylogenetic marker in certain groups, had superior species resolution in some taxonomic groups, such as the early diverging lineages and the ascomycete yeasts, but was otherwise slightly inferior to the ITS. The nuclear ribosomal small subunit has poor species-level resolution in fungi. ITS will be formally proposed for adoption as the primary fungal barcode marker to the Consortium for the Barcode of Life, with the possibility that supplementary barcodes may be developed for particular narrowly circumscribed taxonomic groups

Premise of study: To reliably identify lineages below the species level such as subspecies or varieties, we propose an extension to DNA-barcoding using next-generation sequencing to produce whole organellar genomes and substantial nuclear ribosomal sequence. Because this method uses much longer versions of the traditional DNA-barcoding loci in the plastid and ribosomal DNA, we call our approach ultra-barcoding (UBC). Methods: We used high-throughput next-generation sequencing to scan the genome and generate reliable sequence of high copy number regions. Using this method, we examined whole plastid genomes as well as nearly 6000 bases of nuclear ribosomal DNA sequences for nine genotypes of Theobroma cacao and an individual of the related species T. grandiflorum, as well as an additional publicly available whole plastid genome of T. cacao. Key results: All individuals of T. cacao examined were uniquely distinguished, and evidence of reticulation and gene flow was observed. Sequence variation was observed in some of the canonical barcoding regions between species, but other regions of the chloroplast were more variable both within species and between species, as were ribosomal spacers. Furthermore, no single region provides the level of data available using the complete plastid genome and rDNA. Conclusions: Our data demonstrate that UBC is a viable, increasingly cost-effective approach for reliably distinguishing varieties and even individual genotypes of T. cacao. This approach shows great promise for applications where very closely related or interbreeding taxa must be distinguished.

Documenting the diversity of marine life is challenging because many species are cryptic, small, and rare, and belong to poorly known groups. New sequencing technologies, especially when combined with standardized sampling, promise to make comprehensive biodiversity assessments and monitoring feasible on a large scale. We used this approach to characterize patterns of diversity on oyster reefs across a range of geographic scales comprising a temperate location [Virginia (VA)] and a subtropical location [Florida (FL)]. Eukaryotic organisms that colonized multilayered settlement surfaces (autonomous reef monitoring structures) over a 6-mo period were identified by cytochrome c oxidase subunit I barcoding (>2-mm mobile organisms) and metabarcoding (sessile and smaller mobile organisms). In a total area of ∼15.64 m ² and volume of ∼0.09 m ³, 2,179 operational taxonomic units (OTUs) were recorded from 983,056 sequences. However, only 10.9% could be matched to reference barcodes in public databases, with only 8.2% matching barcodes with both genus and species names. Taxonomic coverage was broad, particularly for animals (22 phyla recorded), but 35.6% of OTUs detected via metabarcoding could not be confidently assigned to a taxonomic group. The smallest size fraction (500 to 106 μm) was the most diverse (more than two-thirds of OTUs). There was little taxonomic overlap between VA and FL, and samples separated by ∼2 m were significantly more similar than samples separated by ∼100 m. Ground-truthing with independent assessments of taxonomic composition indicated that both presence–absence information and relative abundance information are captured by metabarcoding data, suggesting considerable potential for ecological studies and environmental monitoring. Significance High-throughput DNA sequencing methods are revolutionizing our ability to census communities, but most analyses have focused on microbes. Using an environmental DNA sequencing approach based on cytochrome c oxidase subunit 1 primers, we document the enormous diversity and fine-scale geographic structuring of the cryptic animals living on oyster reefs, many of which are rare and very small. Sequence data reflected both the presence and relative abundance of organisms, but only 10.9% of the sequences could be matched to reference barcodes in public databases. These results highlight the enormous numbers of marine animal species that remain genetically unanchored to conventional taxonomy and the importance of standardized, genetically based biodiversity surveys to monitor global change.

Background More than 80% of all animal species remain unknown to science. Most of these species live in the tropics and belong to animal taxa that combine small body size with high specimen abundance and large species richness. For such clades, using morphology for species discovery is slow because large numbers of specimens must be sorted based on detailed microscopic investigations. Fortunately, species discovery could be greatly accelerated if DNA sequences could be used for sorting specimens to species. Morphological verification of such “molecular operational taxonomic units” (mOTUs) could then be based on dissection of a small subset of specimens. However, this approach requires cost-effective and low-tech DNA barcoding techniques because well-equipped, well-funded molecular laboratories are not readily available in many biodiverse countries. Results We here document how MinION sequencing can be used for large-scale species discovery in a specimen- and species-rich taxon like the hyperdiverse fly family Phoridae (Diptera). We sequenced 7059 specimens collected in a single Malaise trap in Kibale National Park, Uganda, over the short period of 8 weeks. We discovered > 650 species which exceeds the number of phorid species currently described for the entire Afrotropical region. The barcodes were obtained using an improved low-cost MinION pipeline that increased the barcoding capacity sevenfold from 500 to 3500 barcodes per flowcell. This was achieved by adopting 1D sequencing, resequencing weak amplicons on a used flowcell, and improving demultiplexing. Comparison with Illumina data revealed that the MinION barcodes were very accurate (99.99% accuracy, 0.46% Ns) and thus yielded very similar species units (match ratio 0.991). Morphological examination of 100 mOTUs also confirmed good congruence with morphology (93% of mOTUs; > 99% of specimens) and revealed that 90% of the putative species belong to the neglected, megadiverse genus Megaselia . We demonstrate for one Megaselia species how the molecular data can guide the description of a new species ( Megaselia sepsioides sp. nov.). Conclusions We document that one field site in Africa can be home to an estimated 1000 species of phorids and speculate that the Afrotropical diversity could exceed 200,000 species. We furthermore conclude that low-cost MinION sequencers are very suitable for reliable, rapid, and large-scale species discovery in hyperdiverse taxa. MinION sequencing could quickly reveal the extent of the unknown diversity and is especially suitable for biodiverse countries with limited access to capital-intensive sequencing facilities.

Land plants underpin a multitude of ecosystem functions, support human livelihoods and represent a critically important component of terrestrial biodiversity—yet many tens of thousands of species await discovery, and plant identification remains a substantial challenge, especially where material is juvenile, fragmented or processed. In this opinion article, we tackle two main topics. Firstly, we provide a short summary of the strengths and limitations of plant DNA barcoding for addressing these issues. Secondly, we discuss options for enhancing current plant barcodes, focusing on increasing discriminatory power via either gene capture of nuclear markers or genome skimming. The former has the advantage of establishing a defined set of target loci maximizing efficiency of sequencing effort, data storage and analysis. The challenge is developing a probe set for large numbers of nuclear markers that works over sufficient phylogenetic breadth. Genome skimming has the advantage of using existing protocols and being backward compatible with existing barcodes; and the depth of sequence coverage can be increased as sequencing costs fall. Its non-targeted nature does, however, present a major informatics challenge for upscaling to large sample sets. This article is part of the themed issue ‘From DNA barcodes to biomes’.

Different distance-based threshold selection approaches were used to assess and compare use of the internal transcribed spacer (ITS) region to distinguish among 901 Cortinarius species represented by >3000 collections. Sources of error associated with genetic markers and selection approaches were explored and evaluated using MOTUs from genus and lineage based-alignments. Our study indicates that 1%–2% more species can be distinguished by using the full-length ITS barcode as compared to either the ITS1 or ITS2 regions alone. Optimal threshold values for different picking approaches and genetic marker lengths inferred from a subset of species containing major lineages ranged from 97.0% to 99.5% sequence similarity using clustering optimization and UNITE SH, and from 1% to 2% sequence dissimilarity with CROP. Errors for the optimal cutoff ranged from 0% to 70%, and these can be reduced to a maximum of 22% when excluding species lacking a barcode gap. A threshold value of 99% is suitable for distinguishing species in the majority of lineages in the genus using the entire ITS region but only 90% of the species could be identified using just the ITS1 or ITS2 region. Prior identification of species, lacking barcode gaps and their subsequent separate analyses, maximized the accuracy of threshold approaches. Fungal DNA barcoding. Graphical Abstract Figure. Fungal DNA barcoding.

Metabarcoding is a powerful molecular tool for simultaneously surveying hundreds to thousands of species from a single sample, underpinning microbiome and environmental DNA (eDNA) methods. Deriving quantitative estimates of underlying biological communities from metabarcoding is critical for enhancing the utility of such approaches for health and conservation. Recent work has demonstrated that correcting for amplification biases in genetic metabarcoding data can yield quantitative estimates of template DNA concentrations. However, a major source of uncertainty in metabarcoding data stems from non-detections across technical PCR replicates where one replicate fails to detect a species observed in other replicates. Such non-detections are a special case of variability among technical replicates in metabarcoding data. While many sampling and amplification processes underlie observed variation in metabarcoding data, understanding the causes of non-detections is an important step in distinguishing signal from noise in metabarcoding studies. Here, we use both simulated and empirical data to 1) suggest how non-detections may arise in metabarcoding data, 2) outline steps to recognize uninformative data in practice, and 3) identify the conditions under which amplicon sequence data can reliably detect underlying biological signals. We show with both simulations and empirical data that, for a given species, the rate of non-detections among technical replicates is a function of both the template DNA concentration and species-specific amplification efficiency. Consequently, we conclude metabarcoding datasets are strongly affected by (1) deterministic amplification biases during PCR and (2) stochastic sampling of amplicons during sequencing—both of which we can model—but also by (3) stochastic sampling of rare molecules prior to PCR, which remains a frontier for quantitative metabarcoding. Our results highlight the importance of estimating species-specific amplification efficiencies and critically evaluating patterns of non-detection in metabarcoding datasets to better distinguish environmental signal from the noise inherent in molecular detections of rare targets.

Amplicon-sequence data from environmental DNA (eDNA) and microbiome studies provide important information for ecology, conservation, management, and health. At present, amplicon-sequencing studies—known also as metabarcoding studies, in which the primary data consist of targeted, amplified fragments of DNA sequenced from many taxa in a mixture—struggle to link genetic observations to the underlying biology in a quantitative way, but many applications require quantitative information about the taxa or systems under scrutiny. As metabarcoding studies proliferate in ecology, it becomes more important to develop ways to make them quantitative to ensure that their conclusions are adequately supported. Here we link previously disparate sets of techniques for making such data quantitative, showing that the underlying polymerase chain reaction mechanism explains the observed patterns of amplicon data in a general way. By modeling the process through which amplicon-sequence data arise, rather than transforming the data post hoc, we show how to estimate the starting DNA proportions from a mixture of many taxa. We illustrate how to calibrate the model using mock communities and apply the approach to simulated data and a series of empirical examples. Our approach opens the door to improve the use of metabarcoding data in a wide range of applications in ecology, public health, and related fields.

Transposon mutagenesis with next-generation sequencing (TnSeq) is a powerful approach to annotate gene function in bacteria, but existing protocols for TnSeq require laborious preparation of every sample before sequencing. Thus, the existing protocols are not amenable to the throughput necessary to identify phenotypes and functions for the majority of genes in diverse bacteria. Here, we present a method, random bar code transposon-site sequencing (RB-TnSeq), which increases the throughput of mutant fitness profiling by incorporating random DNA bar codes into Tn 5 and mariner transposons and by using bar code sequencing (BarSeq) to assay mutant fitness. RB-TnSeq can be used with any transposon, and TnSeq is performed once per organism instead of once per sample. Each BarSeq assay requires only a simple PCR, and 48 to 96 samples can be sequenced on one lane of an Illumina HiSeq system. We demonstrate the reproducibility and biological significance of RB-TnSeq with Escherichia coli , Phaeobacter inhibens , Pseudomonas stutzeri , Shewanella amazonensis , and Shewanella oneidensis . To demonstrate the increased throughput of RB-TnSeq, we performed 387 successful genome-wide mutant fitness assays representing 130 different bacterium-carbon source combinations and identified 5,196 genes with significant phenotypes across the five bacteria. In P. inhibens , we used our mutant fitness data to identify genes important for the utilization of diverse carbon substrates, including a putative d -mannose isomerase that is required for mannitol catabolism. RB-TnSeq will enable the cost-effective functional annotation of diverse bacteria using mutant fitness profiling. IMPORTANCE A large challenge in microbiology is the functional assessment of the millions of uncharacterized genes identified by genome sequencing. Transposon mutagenesis coupled to next-generation sequencing (TnSeq) is a powerful approach to assign phenotypes and functions to genes. However, the current strategies for TnSeq are too laborious to be applied to hundreds of experimental conditions across multiple bacteria. Here, we describe an approach, random bar code transposon-site sequencing (RB-TnSeq), which greatly simplifies the measurement of gene fitness by using bar code sequencing (BarSeq) to monitor the abundance of mutants. We performed 387 genome-wide fitness assays across five bacteria and identified phenotypes for over 5,000 genes. RB-TnSeq can be applied to diverse bacteria and is a powerful tool to annotate uncharacterized genes using phenotype data. A large challenge in microbiology is the functional assessment of the millions of uncharacterized genes identified by genome sequencing. Transposon mutagenesis coupled to next-generation sequencing (TnSeq) is a powerful approach to assign phenotypes and functions to genes. However, the current strategies for TnSeq are too laborious to be applied to hundreds of experimental conditions across multiple bacteria. Here, we describe an approach, random bar code transposon-site sequencing (RB-TnSeq), which greatly simplifies the measurement of gene fitness by using bar code sequencing (BarSeq) to monitor the abundance of mutants. We performed 387 genome-wide fitness assays across five bacteria and identified phenotypes for over 5,000 genes. RB-TnSeq can be applied to diverse bacteria and is a powerful tool to annotate uncharacterized genes using phenotype data.

A two-marker combination of plastid rbcL and matK has previously been recommended as the core plant barcode, to be supplemented with additional markers such as plastid trnH–psbA and nuclear ribosomal internal transcribed spacer (ITS). To assess the effectiveness and universality of these barcode markers in seed plants, we sampled 6,286 individuals representing 1,757 species in 141 genera of 75 families (42 orders) by using four different methods of data analysis. These analyses indicate that (i) the three plastid markers showed high levels of universality (87.1–92.7%), whereas ITS performed relatively well (79%) in angiosperms but not so well in gymnosperms; (ii) in taxonomic groups for which direct sequencing of the marker is possible, ITS showed the highest discriminatory power of the four markers, and a combination of ITS and any plastid DNA marker was able to discriminate 69.9–79.1% of species, compared with only 49.7% with rbcL + matK; and (iii) where multiple individuals of a single species were tested, ascriptions based on ITS and plastid DNA barcodes were incongruent in some samples for 45.2% of the sampled genera (for genera with more than one species sampled). This finding highlights the importance of both sampling multiple individuals and using markers with different modes of inheritance. In cases where it is difficult to amplify and directly sequence ITS in its entirety, just using ITS2 is a useful backup because it is easier to amplify and sequence this subset of the marker. We therefore propose that ITS/ITS2 should be incorporated into the core barcode for seed plants.