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

phyloBARCODER: A Web Tool for Phylogenetic Classification of Eukaryote Metabarcodes Using Custom Reference Databases

We developed phyloBARCODER (https://github.com/jun-inoue/phyloBARCODER), a new web tool that can identify short DNA sequences to the species level using metabarcoding. phyloBARCODER estimates phylogenetic trees based on the uploaded anonymous DNA sequences and reference sequences from databases. Without such phylogenetic contexts, alternative, similarity-based methods independently identify species names and anonymous sequences of the same group by pairwise comparisons between queries and database sequences, with the caveat that they must match exactly or very closely. By putting metabarcoding sequences into a phylogenetic context, phyloBARCODER accurately identifies (i) species or classification of query sequences and (ii) anonymous sequences associated with the same species or even with populations of query sequences, with clear and accurate explanations. Version 1 of phyloBARCODER stores a database comprising all eukaryotic mitochondrial gene sequences. Moreover, by uploading their own databases, phyloBARCODER users can conduct species identification specialized for sequences obtained from a local geographic region or those of nonmitochondrial genes, e.g. ITS or rbcL.

Principles for Constructing DNA Barcode Reference Libraries

All DNA barcode methods rely on reference sequences linked to well-curated voucher specimens. Definitions for and locations of DNA barcode reference libraries are not standardized, and vary throughout the literature. Standardizing, and centralizing reference specimens would provide an unambiguous source, analogous to reference genomes, to reproduce identifications and improve a library. This chapter proposes a working definition of a DNA barcode reference library, consistent with DNA barcode data standards, along with principles and methods to consider when producing or using such a library. These methods allow explicit traceback to sequence-sources which elevate the value of voucher specimens, and create a potential for community curation.

I Like This New Me: Unravelling Population Structure of Mediterranean Electric Rays and Taxonomic Uncertainties within Torpediniformes

The present study focused on the three species of electric rays known to occur in the Mediterranean Sea: Torpedo torpedo, Torpedo marmorata and Tetronarce nobiliana. Correct identification of specimens is needed to properly assess the impact of fisheries on populations and species. Unfortunately, torpedoes share high morphological similarities, boosting episodes of field misidentification. In this context, genetic data was used (1) to identify specimens caught during fishing operations, (2) to measure the diversity among and within these species, and (3) to shed light on the possible occurrence of additional hidden species in the investigated area. New and already published sequences of COI and NADH2 mitochondrial genes were analyzed, both at a small scale along the Sardinian coasts (Western Mediterranean) and at a large scale in the whole Mediterranean Sea. High levels of genetic diversity were found in Sardinian populations, being significantly different from other areas of the Eastern Mediterranean Sea due to the biotic and abiotic factors here discussed. Sardinian torpedoes can hence be indicated as priority populations/areas to be protected within the Mediterranean Sea. Moreover, sequence data confirmed that only the three species occur in the investigated area. The application of several 'species-delimitation' methods found evidence of cryptic species in the three species outside the Mediterranean Sea, as well as in other genera/families, suggesting the urgent need for future studies and a comprehensive revision of the order Torpediniformes for its effective conservation.

A comparison of biomonitoring methodologies for surf zone fish communities

Surf zones are highly dynamic marine ecosystems that are subject to increasing anthropogenic and climatic pressures, posing multiple challenges for biomonitoring. Traditional methods such as seines and hook and line surveys are often labor intensive, taxonomically biased, and can be physically hazardous. Emerging techniques, such as baited remote underwater video (BRUV) and environmental DNA (eDNA) are promising nondestructive tools for assessing marine biodiversity in surf zones of sandy beaches. Here we compare the relative performance of beach seines, BRUV, and eDNA in characterizing community composition of bony (teleost) and cartilaginous (elasmobranch) fishes of surf zones at 18 open coast sandy beaches in southern California. Seine and BRUV surveys captured overlapping, but distinct fish communities with 50% (18/36) of detected species shared. BRUV surveys more frequently detected larger species (e.g. sharks and rays) while seines more frequently detected one of the most abundant species, barred surfperch (Amphistichus argenteus). In contrast, eDNA metabarcoding captured 88.9% (32/36) of all fishes observed in seine and BRUV surveys plus 57 additional species, including 15 that frequent surf zone habitats. On average, eDNA detected over 5 times more species than BRUVs and 8 times more species than seine surveys at a given site. eDNA approaches also showed significantly higher sensitivity than seine and BRUV methods and more consistently detected 31 of the 32 (96.9%) jointly observed species across beaches. The four species detected by BRUV/seines, but not eDNA were only resolved at higher taxonomic ranks (e.g. Embiotocidae surfperches and Sygnathidae pipefishes). In frequent co-detection of species between methods limited comparisons of richness and abundance estimates, highlighting the challenge of comparing biomonitoring approaches. Despite potential for improvement, results overall demonstrate that eDNA can provide a cost-effective tool for long-term surf zone monitoring that complements data from seine and BRUV surveys, allowing more comprehensive surveys of vertebrate diversity in surf zone habitats.

crabs-A software program to generate curated reference databases for metabarcoding sequencing data

The measurement of biodiversity is an integral aspect of life science research. With the establishment of second- and third-generation sequencing technologies, an increasing amount of metabarcoding data is being generated as we seek to describe the extent and patterns of biodiversity in multiple contexts. The reliability and accuracy of taxonomically assigning metabarcoding sequencing data have been shown to be critically influenced by the quality and completeness of reference databases. Custom, curated, eukaryotic reference databases, however, are scarce, as are the software programs for generating them. Here, we present crabs (Creating Reference databases for Amplicon-Based Sequencing), a software package to create custom reference databases for metabarcoding studies. crabs includes tools to download sequences from multiple online repositories (i.e., NCBI, BOLD, EMBL, MitoFish), retrieve amplicon regions through in silico PCR analysis and pairwise global alignments, curate the database through multiple filtering parameters (e.g., dereplication, sequence length, sequence quality, unresolved taxonomy, inclusion/exclusion filter), export the reference database in multiple formats for immediate use in taxonomy assignment software, and investigate the reference database through implemented visualizations for diversity, primer efficiency, reference sequence length, database completeness and taxonomic resolution. crabs is a versatile tool for generating curated reference databases of user-specified genetic markers to aid taxonomy assignment from metabarcoding sequencing data. crabs can be installed via docker and is available for download as a conda package and via GitHub (https://github.com/gjeunen/reference_database_creator).

Maximizing the reliability and the number of species assignments in metabarcoding studies using a curated regional library and a public repository

Biodiversity assessments relying on DNA have increased rapidly over the last decade. However, the reliability of taxonomic assignments in metabarcoding studies is variable and affected by the reference databases and the assignment methods used. Species level assignments are usually considered as reliable using regional libraries but unreliable using public repositories. In this study, we aimed to test this assumption for metazoan species detected in the Gulf of St. Lawrence in the Northwest Atlantic. We first created a regional library (GSL-rl) by data mining COI barcode sequences from BOLD, and included a reliability ranking system for species assignments. We then estimated 1) the accuracy and precision of the public repository NCBI-nt for species assignments using sequences from the regional library and 2) compared the detection and reliability of species assignments of a metabarcoding dataset using either NCBI-nt or the regional library and popular assignment methods. With NCBI-nt and sequences from the regional library, the BLAST-LCA (least common ancestor) method was the most precise method for species assignments, but the accuracy was higher with the BLAST-TopHit method (>80% over all taxa, between 70% and 90% amongst taxonomic groups). With the metabarcoding dataset, the reliability of species assignments was greater using GSL-rl compared to NCBI-nt. However, we also observed that the total number of reliable species assignments could be maximized using both GSL-rl and NCBI-nt with different optimized assignment methods. The use of a two-step approach for species assignments, i.e., using a regional library and a public repository, could improve the reliability and the number of detected species in metabarcoding studies.

Be positive: customized reference databases and new, local barcodes balance false taxonomic assignments in metabarcoding studies

Background

In metabarcoding analyses, the taxonomic assignment is crucial to place sequencing data in biological and ecological contexts. This fundamental step depends on a reference database, which should have a good taxonomic coverage to avoid unassigned sequences. However, this goal is rarely achieved in many geographic regions and for several taxonomic groups. On the other hand, more is not necessarily better, as sequences in reference databases belonging to taxonomic groups out of the studied region/environment context might lead to false assignments.

Methods

We investigated the effect of using several subsets of a cytochrome c oxidase subunit I (COI) reference database on taxonomic assignment. Published metabarcoding sequences from the Mediterranean Sea were assigned to taxa using COInr, which is a comprehensive, non-redundant and recent database of COI sequences obtained both from BOLD and NCBI, and two of its subsets: (i) all sequences except insects (COInr-WO-Insecta), which represent the overwhelming majority of COInr database, but are irrelevant for marine samples, and (ii) all sequences from taxonomic families present in the Mediterranean Sea (COInr-Med). Four different algorithms for taxonomic assignment were employed in parallel to evaluate differences in their output and data consistency.

Results

The reduction of the database to more specific custom subsets increased the number of unassigned sequences. Nevertheless, since most of them were incorrectly assigned by the less specific databases, this is a positive outcome. Moreover, the taxonomic resolution (the lowest taxonomic level to which a sequence is attributed) of several sequences tended to increase when using customized databases. These findings clearly indicated the need for customized databases adapted to each study. However, the very high proportion of unassigned sequences points to the need to enrich the local database with new barcodes specifically obtained from the studied region and/or taxonomic group. Including novel local barcodes to the COI database proved to be very profitable: by adding only 116 new barcodes sequenced in our laboratory, thus increasing the reference database by only 0.04%, we were able to improve the resolution for ca. 0.6-1% of the Amplicon Sequence Variants (ASVs).

Signal and noise in metabarcoding data

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.

Fishing for fish environmental DNA: Ecological applications, methodological considerations, surveying designs, and ways forward

Vast global declines of freshwater and marine fish diversity and population abundance pose serious threats to both ecosystem sustainability and human livelihoods. Environmental DNA (eDNA)-based biomonitoring provides robust, efficient, and cost-effective assessment of species occurrences and population trends in diverse aquatic environments. Thus, it holds great potential for improving conventional surveillance frameworks to facilitate fish conservation and fisheries management. However, the many technical considerations and rapid developments underway in the eDNA arena can overwhelm researchers and practitioners new to the field. Here, we systematically analysed 416 fish eDNA studies to summarize research trends in terms of investigated targets, research aims, and study systems, and reviewed the applications, rationales, methodological considerations, and limitations of eDNA methods with an emphasis on fish and fisheries research. We highlighted how eDNA technology may advance our knowledge of fish behaviour, species distributions, population genetics, community structures, and ecological interactions. We also synthesized the current knowledge of several important methodological concerns, including the qualitative and quantitative power eDNA has to recover fish biodiversity and abundance, and the spatial and temporal representations of eDNA with respect to its sources. To facilitate ecological applications implementing fish eDNA techniques, recent literature was summarized to generate guidelines for effective sampling in lentic, lotic, and marine habitats. Finally, we identified current gaps and limitations, and pointed out newly emerging research avenues for fish eDNA. As methodological optimization and standardization improve, eDNA technology should revolutionize fish monitoring and promote biodiversity conservation and fisheries management that transcends geographic and temporal boundaries.

Metagenomic Analysis Using Phylogenetic Placement-A Review of the First Decade

Phylogenetic placement refers to a family of tools and methods to analyze, visualize, and interpret the tsunami of metagenomic sequencing data generated by high-throughput sequencing. Compared to alternative (e. g., similarity-based) methods, it puts metabarcoding sequences into a phylogenetic context using a set of known reference sequences and taking evolutionary history into account. Thereby, one can increase the accuracy of metagenomic surveys and eliminate the requirement for having exact or close matches with existing sequence databases. Phylogenetic placement constitutes a valuable analysis tool per se, but also entails a plethora of downstream tools to interpret its results. A common use case is to analyze species communities obtained from metagenomic sequencing, for example via taxonomic assignment, diversity quantification, sample comparison, and identification of correlations with environmental variables. In this review, we provide an overview over the methods developed during the first 10 years. In particular, the goals of this review are 1) to motivate the usage of phylogenetic placement and illustrate some of its use cases, 2) to outline the full workflow, from raw sequences to publishable figures, including best practices, 3) to introduce the most common tools and methods and their capabilities, 4) to point out common placement pitfalls and misconceptions, 5) to showcase typical placement-based analyses, and how they can help to analyze, visualize, and interpret phylogenetic placement data.