Genetic diversity is estimated to be declining faster than species diversity under escalating threats, but its spatial distribution remains poorly documented at the global scale. Theory predicts that similar processes should foster congruent spatial patterns of genetic and species diversity, but empirical studies are scarce. Using a mined database of 50,588 georeferenced mitochondrial DNA barcode sequences (COI) for 3,815 marine and 1,611 freshwater fish species respectively, we examined the correlation between genetic diversity and species diversity and their global distributions in relation to climate and geography. Genetic diversity showed a clear spatial organisation, but a weak association with species diversity for both marine and freshwater species. We found a predominantly positive relationship between genetic diversity and sea surface temperature for marine species. Genetic diversity of freshwater species varied primarily across the regional basins and was negatively correlated with average river slope. The detection of genetic diversity patterns suggests that conservation measures should consider mismatching spatial signals across multiple facets of biodiversity.

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.

Aim: Coastal fishes have a fundamental role in marine ecosystem functioning and contributions to people, but face increasing threats due to climate change, habitat degradation and overexploitation. The extent to which human pressures are impacting coastal fish biodiversity in comparison with geographic and environmental factors at large spatial scale is still under scrutiny. Here, we took advantage of environmental DNA (eDNA) metabarcoding to investigate the relationship between fish biodiversity, including taxonomic and genetic components, and environmental but also socio‐economic factors.Location: Tropical, temperate and polar coastal areas.Time period: Present day.Major taxa studied: Marine fishes.Methods: We analysed fish eDNA in 263 stations (samples) in 68 sites distributed across polar, temperate and tropical regions. We modelled the effect of environmental, geographic and socio‐economic factors on α‐ and β‐diversity. We then computed the partial effect of each factor on several fish biodiversity components using taxonomic molecular units (MOTU) and genetic sequences. We also investigated the relationship between fish genetic α‐ and β‐diversity measured from our barcodes, and phylogenetic but also functional diversity.Results: We show that fish eDNA MOTU and sequence α‐ and β‐diversity have the strongest correlation with environmental factors on coastal ecosystems worldwide. However, our models also reveal a negative correlation between biodiversity and human dependence on marine ecosystems. In areas with high dependence, diversity of all fish, cryptobenthic fish and large fish MOTUs declined steeply. Finally, we show that a sequence diversity index, accounting for genetic distance between pairs of MOTUs, within and between communities, is a reliable proxy of phylogenetic and functional diversity.Main conclusions: Together, our results demonstrate that short eDNA sequences can be used to assess climate and direct human impacts on marine biodiversity at large scale in the Anthropocene and can further be extended to investigate biodiversity in its phylogenetic and functional dimensions.

Protein structure prediction based on comparative modeling is the most efficient way to produce structural models when it can be performed. ORION is a dedicated webserver based on a new strategy that performs this task. The identification by ORION of suitable templates is performed using an original profile-profile approach that combines sequence and structure evolution information. Structure evolution information is encoded into profiles using structural features, such as solvent accessibility and local conformation —with Protein Blocks—, which give an accurate description of the local protein structure. ORION has recently been improved, increasing by 5% the quality of its results. The ORION web server accepts a single protein sequence as input and searches homologous protein structures within minutes. Various databases such as PDB, SCOP and HOMSTRAD can be mined to find an appropriate structural template. For the modeling step, a protein 3D structure can be directly obtained from the selected template by MODELLER and displayed with global and local quality model estimation measures. The sequence and the predicted structure of 4 examples from the CAMEO server and a recent CASP11 target from the ‘Hard’ category (T0818-D1) are shown as pertinent examples. Our web server is accessible athttp://www.dsimb.inserm.fr/ORION/.

Environmental DNA is mainly not only used at the interspecific level, to quantify species diversity in ecosystems, but can also be used to quantify intraspecific genetic variability, thus avoiding the need to sample individual tissue. However, errors in the amplification and sequencing of eDNA samples can blur this intraspecific signal and strongly over‐estimate genetic diversity. Existing bioinformatics pipelines therefore need to be tested to evaluate whether reliable levels of intraspecific genetic variability can be derived from eDNA samples. Here, we compare the ability of twelve metabarcoding pipelines to detect intraspecific genetic variability combining five programs. All pipelines have common pre‐processing steps, a processing data step using programs among obiclean; DADA2; SWARM; and LULU. An additional chimera removal step is also investigated based on two programs (VSEARCH or DADA2). The case study was the natural intraspecific variation within Mullus surmuletus in experimental settings. We developed specific primers for this species, located on the mitochondrial D‐loop fragment (barcode MS‐DL06). Thirty‐nine individuals were collected from the Mediterranean Sea, placed into four aquariums, and their DNA was sequenced on this marker to build an intraspecific reference database. After filtering the aquarium water, DNA was extracted, amplified, and sequenced using the primer pair developed. We then quantified the number of true haplotypes returned by each pipeline and its capacity to eliminate most of the erroneous sequences. We show that the program DADA2 with a two‐parent chimeric sequence removal step is the best tool to estimate intraspecific diversity from eDNA. Furthermore, our approach was also able to detect true M. surmuletus haplotypes in two eDNA samples collected in the Mediterranean Sea. We conclude that the combination of an appropriate intrapopulation barcode and a denoising pipeline like DADA2 with a chimeric sequence removal step is promising to make population‐level inference using environmental DNA possible.