In recent years, environmental DNA (eDNA) coupled with metabarcoding methodologies has emerged as a promising tool with the potential to improve biodiversity assessment, diet analysis, detection of rare or invasive species, population genetics, and ecosystem functional analysis (Bohmann et al., 2014; Goldberg et al., 2015). eDNA is a complex mixture of genomic DNA from many organisms found in an environment, wherefore DNA is extracted from an environmental sample without accessing the target organism (Lodge et al., 2012; Taberlet et al., 2012a). In general, the eDNA approach involves a series of steps that include eDNA capture, preservation, extraction, amplification, and sequencing to ensure match to target species. Several types of samples have already been used to recover eDNA, including water, soil, feces, pollen, and air (Taberlet et al., 2012a; Deiner et al., 2015). Nevertheless, marine environments are probably the most challenging and difficult aquatic environments for applying the eDNA method. This is because of the extreme water-volume to biomass ratio, the effects of sea currents and wave action on dispersion and dilution of eDNA, and the impact of salinity on the preservation and extraction of eDNA (Thomsen et al., 2012a). eDNA detection features create uncertainty; hence its characterization and appropriate use requires better understanding of eDNA in four domains: origin, state, transport, and fate (Turner et al., 2015). DNA in environmental samples is typically highly degraded into fragments of often less than 150 base pairs (Deagle et al., 2006) and is not always easy to extract. Degradation of eDNA in the environment limits the scope of eDNA studies, as often only small segments of genetic material remain (Turner et al., 2014). eDNA concentration is dependent on biomass, age, and feeding activity of organisms, as well as physiology, life history, and space use (Barnes et al., 2014; Goldberg et al., 2016). Mitochondrial DNA is typically targeted because there are a great number of copies compared to nuclear DNA, its effectiveness in identifying organism to the species level by means of DNA barcoding, including in fish, and its accessibility via universal sequence databases on public servers (e.g. GENBANK and Bold Systems) (Rees et al., 2014). Amplified mitochondrial eDNA may originate from extracellular DNA fragments, mitochondria, cells, excretion, or eggs, and the amount of eDNA quantified is likely to vary depending on the genetic matter being targeted (Herder et al., 2014; Goldberg et al., 2016). A crucial step in the eDNA workflow is DNA capture. Several studies focus on optimization of sampling design and eDNA capture and extraction methods (e.g. Turner et al., 2014; Deiner et al., 2015, Eichmiller et al., 2016). Collection methods typically seek to identify organisms at low densities and, thus, should be optimized for detection sensitivity. Because of this, multiple protocols have been developed in the literature and may be applied to different types of samples (e.g. Turner et al., 2014; Deiner et al., 2015); however, protocol election needs to be carefully considered depending on the goals of the study and the type of sample being analyzed. eDNA extraction protocols that are being optimized within the frame of the FishGenome project target three main applications: single species detection, estimation of abundance and biomass of target species, and biodiversity assessment. The FishGenome project will use two main methods to analyze eDNA: High-Throughput Sequencing (HTS) for biodiversity assessment, and quantitative Polymerase Chain Reaction (qPCR) for the quantification of a target species. For the HTS method, both universal and species-specific primers may be used, but this will depend on the goal of the study. Power of detection will depend on the affinity to the targeted taxa sequences and the availability of DNA reference collection databases needed for species identification. HTS is mostly used to detect multiple species and for biodiversity assessment. Meanwhile, qPCR is widely used for gene expression analysis due to its large dynamic range, tremendous sensitivity, high sequence specificity, little to no postamplification processing, and sample throughput (Lodge et al., 2012). This method is usually performed for species detection and involves the use of species-specific primer sets; it also allows the quantification of target species DNA, which has been shown to correlate with species abundance and biomass in the environment (Lodge et al., 2012; Thomsen et al., 2012a). Since eDNA is a sensitive method, there are many potential sources of “errors”. Some of these errors, which are associated to collecting, laboratory, and bioinformatic procedures, are: contamination, inhibition, amplification and sequencing errors, computational artifacts, and inaccurate taxonomic assignment (Thomsen et al., 2016; Barnes and Turner 2016). Out of these errors, the most serious is probably the risk of contamination and hence the possibility of false positive results. The use and sensitivity of HTS has further complicated the contamination issue, as a very high throughput of DNA sequences is produced (Ficetola et al. 2016). Thus, understanding potential sources of errors and translating these into methodological protocols and interpretations of the results is crucial for reliable outcomes. Along these lines, eDNA offers a potential method to revolutionize marine biomonitoring by significantly augmenting spatial and temporal biological monitoring in aquatic ecosystems due to the ease of collecting water samples (Thomsen and Willerslev, 2015; Sassoubre et al., 2016). eDNA also has the potential to advance fisheries monitoring and conservation by improving detection-probabilities for rare fishes that often comprise a large proportion of the total species richness found in species assemblages. The non-invasive nature of eDNA analysis may provide advantages over traditional capture-based sampling by making it possible to determine the presence or absence of species without disturbance to the fish or their environment. This approach could be especially beneficial in situations of endangered species, where there is significant risk of injury to fishes or damage to their critical habitat (Evans and Lamberti, 2018). More investigations are required in order to understand how well the eDNA method will work for aquatic species, to evaluate the effect of species abundance on detection efficiency, and to upscale species detection from local water samples to larger spatial areas, such as drainage basins. However, it is challenging to work with such small amounts of DNA.

FishGenome is developed under the contract EASME/EMFF/2018/015: “Improving Cost-Efficiency of Fisheries Research Surveys and Fish Stocks Assessments using Next-Generation Genetic Sequencing Methods”, financed by the Union’s budget

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