Blind assessment of vertebrate taxonomic diversity across spatial scales by clustering environmental DNA metabarcoding sequences

Abstract

Human activities impact all ecosystems on Earth, which urges scientists to better understand biodiversity changes across temporal and spatial scales. Environmental DNA (eDNA) metabarcoding is a promising non‐invasive method to assess species composition in a wide range of ecosystems. Yet, this method requires the completeness of a reference database, i.e. a list of DNA sequences attached to each species of the regional pool, which is rarely met. As an alternative, molecular operational taxonomic units (MOTUs) can be extracted as clusters of sequences. However, the extent to which the diversity of MOTUs can predict the diversity of species across spatial scales is unknown. Here, we used 196 samples along the Rhone river (France) for which the reference database is complete to assess whether a blind eDNA approach can reliably predict the ground‐truth number of species at different spatial scales. Using the 12S rDNA teleo primer, we curated and clustered 60 million sequences into MOTUs using a new assembled bioinformatic pipeline. We show that stringent quality filters were necessary to remove artefact noise, notably MOTUs present in a single PCR replicate, which represented 55% of MOTUs (103). Post‐clustering cleaning also removed 19 additional erroneous MOTUs and only discarded one truly present species. We then show that the diversity of retained fish MOTUs accurately predicted the local (α, r = 0.98) and regional (γ) ground‐truth species diversity (67 MOTUs versus 63 species), but also the species dissimilarity between samples (β‐diversity, r = 0.98). This work paves the way towards extending the use of eDNA metabarcoding in community ecology and biogeography despite major gaps in genetic reference databases.

The critical role of natural history museums in advancing eDNA for biodiversity studies: a case study with Amazonian fishes

“…It corroborates a recent global gap analysis of reference databases (Marques et al, 2020: figure 1), which revealed that 13% of the over 33,000 known teleostean fish species are sequenced for 12S, representing 38% of genera, 80% of families and 98.5% of orders. For freshwater fishes, among all continents, South America and Africa had by far the lowest coverage.…”

“…Concomitant with sampling and curating efforts, new public platforms have been created to help close gaps in shared sample information (e.g., Global Genome Biodiversity Network, Droege et al, 2016) and facilitate access to the sequences (e.g., BOLD). In contrast to this trend, historically few efforts to collect a substantial number of tissue samples during ichthyological surveys -possibly because of the lack of infrastructure to maintain such a collection -results in a lack of robust reference libraries for Amazonian fishes (e.g., Marques et al, 2020). In addition, despite recognizing that Genbank is a reliable resource (Leray et al, 2019), several samples of Amazonian fishes are poorly identified in GenBank and/or lack of properly preserved voucher specimens -a problem that extends to other fishes (e.g., Dillman et al, 2014;Sidharthan et al, 2021).…”

Comparing environmental DNA metabarcoding and underwater visual census to monitor tropical reef fishes

“…We performed the aggregation into MOTUs using the teleo primers, as the bioinformatics clustering pipeline using SWARM has only been developed and fully tested with this primer (Juhel et al., 2020; Marques et al., 2020). In Providencia, the eDNA clustering pipeline identified 227 distinct MOTUs, and we detected an average of 26.2 ± 12.6 MOTUs per filter.…”

How many replicates to accurately estimate fish biodiversity using environmental DNA on coral reefs?

“…eDNA-based methods rely on the detection of DNA fragments from various sources including faeces, shed skin cells, organelles, or extruded waste of animals, which become suspended in the water (Dejean et al ., 2012; Collins et al ., 2018; Harrison, Sunday and Rogers, 2019). Using filtered water and molecular analyses, eDNA metabarcoding can estimate biodiversity across kingdoms at different taxonomic levels without isolating any target organisms (Valentini et al ., 2016; Holman et al ., 2021), and even without exhaustive genetic reference databases (Flynn et al ., 2015; Juhel et al ., 2020; Marques et al ., 2020, 2021). Overall, eDNA metabarcoding has the potential to overcome some limitations of common sampling methods by targeting complete species assemblages, detecting rare (Rees et al ., 2014), elusive (Boussarie et al ., 2018) or non-indigenous species (Ficetola et al ., 2008; Holman et al ., 2019) and is harmless to organisms and less time-consuming (Bohmann et al ., 2014; Smart et al ., 2016).…”