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Over the past decades the sampling of environmental DNA (eDNA) — encompassing the DNA of all organisms present in an environmental sample1 — has emerged as a technique for biodiversity monitoring and discovery in a diversity of environments. Avoiding the physical collection and identification of biota, this approach is praised for its independence of taxonomic expertise and has changed the way biologists study biodiversity. However, a common result in eDNA studies is the finding of unexpected taxa which are often removed by conservative bioinformatic filters or disregarded, since the authors are uncertain about the result and rarely have the interest, time, skills, and/or resources to return to the field and confirm with actual specimens2. Here, we report a case in which an eDNA discovery led to the physical localization of a member of the Micrognathozoa (Figure 1B) — a rare group of limnic micrometazoans, and the animal phylum to be discovered last3, which is the sister group to rotifers4,5. To this day, Micrognathozoa still comprises only a single named species from Greenland and a few additional disparate places

Information about the dietary composition of a species is crucial to understanding their position and role in the food web. Increasingly, molecular approaches such as DNA metabarcoding are used in studying trophic relationships, not least because they may alleviate problems such as low taxonomic resolution or underestimation of digestible taxa in the diet. Here, we used DNA metabarcoding with universal primers for cytochrome c oxidase I (COI) to study the diet composition of the northern shrimp (Pandalus borealis), an Arctic keystone species with large socio-economic importance. Across locations, jellyfish and chaetognaths were the most important components in the diet of P. borealis, jointly accounting for 40%–60% of the total read abundance. This dietary importance of gelatinous zooplankton contrasts sharply with published results based on stomach content analysis. At the same time, diet composition differed between fjord and shelf locations, pointing to different food webs supporting P. borealis in these two systems. Our study underlines the potential of molecular approaches to provide new insights into the diet of marine invertebrates that are difficult to obtain with traditional methods, and calls for a revision of the role of gelatinous zooplankton in the diet of the key Arctic species P. borealis, and in extension, Arctic food webs.

Ecosystem biomonitoring is crucial for proper management of natural communities during the Anthropocene era. With the advent of new sequencing technologies, DNA metabarcoding has been proposed as a game-changing tool for biomonitoring. In this Thesis we plead for the use of metabarcoding of a highly variable marker to infer not only the interspecies but also the intraspecies variability to assess both biogeographic, at the species level, and metaphylogeographic patterns, at the haplotype level. We focused on highly complex hard-substratum benthic littoral communities. The term "Metaphylogeography", coined in this Thesis, refers to the study of phylogeographic patterns of many species at the same time using metabarcoding data. However, as of the start of this Thesis, only a few studies had tested the metabarcoding method to directly characterize the whole eukaryotic community in highly diverse benthic ecosystems. This required to set up and calibrate methods for these communities as a prior step. We first evaluated both the sampling methods and the bioinformatic pipelines. We assessed the viability of detecting the environmental DNA released from the benthic community into the adjacent water layer using metabarcoding of COI with highly degenerated primers targeting the whole eukaryotic community. We sampled water from 0 to 20m from shallow rocky benthic communities and compared the DNA signal with the results obtained from metabarcoding directly the benthic communities by traditional quadrat sampling. We also designed a pipeline combining clustering and denoising methods to treat metabarcoding data of COI. We considered the entropy of each codon position of this coding fragment both to improve the detection of spurious sequences and to calibrate the best performing parameters of the software used. In addition, we created our own denoising program, DnoisE, to incorporate information on the codon position. This new code and parameter calibration were required as the co

DNA metabarcoding is broadly used in biodiversity studies encompassing a wide range of organisms. Erroneous amplicons, generated during amplification and sequencing procedures, constitute one of the major sources of concern for the interpretation of metabarcoding results. Several denoising programs have been implemented to detect and eliminate these errors. However, almost all denoising software currently available has been designed to process non-coding ribosomal sequences, most notably prokaryotic 16S rDNA. The growing number of metabarcoding studies using coding markers such as COI or RuBisCO demands a re-assessment and calibration of denoising algorithms. Here we present DnoisE, the first denoising program designed to detect erroneous reads and merge them with the correct ones using information from the natural variability (entropy) associated to each codon position in coding barcodes. We have developed an open-source software using a modified version of the UNOISE algorithm. DnoisE implements different merging procedures as options, and can incorporate codon entropy information either retrieved from the data or supplied by the user. In addition, the algorithm of DnoisE is parallelizable, greatly reducing runtimes on computer clusters. Our program also allows different input file formats, so it can be readily incorporated into existing metabarcoding pipelines.

Traditional morphological methods for species identification are highly time consuming, especially for small organisms, such as Foraminifera, a group of shell-building microbial eukaryotes. To analyze large amounts of samples more efficiently, species identification methods have extended to molecular tools in the last few decades. Although a wide range of phyla have good markers available, for Foraminifera only one hypervariable marker from the ribosomal region (18S) is widely used. Recently a new mitochondrial marker cytochrome oxidase subunit 1 (COI) has been sequenced. Here we investigate whether this marker has a higher potential for species identification compared to the ribosomal marker. We explore the genetic variability of both the 18S and COI markers in 22 benthic foraminiferal morphospecies (orders Miliolida and Rotaliida). Using single-cell DNA, the genetic variability within specimens (intra) and between specimens (inter) of each species was assessed using next-generation sequencing. Amplification success rate was twice as high for COI (151/200 specimens) than for 18S (73/200 specimens). The COI marker showed greatly decreased intra- and inter-specimen variability compared to 18S in six out of seven selected species. The 18S phylogenetic reconstruction fails to adequately cluster multiple species together in contrast to COI. Additionally, the COI marker helped recognize misclassified specimens difficult to morphologically identify to the species level. Integrative taxonomy, combining morphological and molecular characteristics, provides a robust picture of the foraminiferal species diversity. Finally, we suggest the use of a set of sequences (two or more) to describe species showing intra-genomic variability additionally to using multiple markers. Our findings highlight the potential of the newly discovered mitochondrial marker for molecular species identification and metabarcoding purposes.