Restriction‐site‐associated DNA sequencing (RAD‐seq) and related methods are revolutionizing the field of population genomics in nonmodel organisms as they allow generating an unprecedented number of single nucleotide polymorphisms (SNPs) even when no genomic information is available. Yet, RAD‐seq data analyses rely on assumptions on nature and number of nucleotide variants present in a single locus, the choice of which may lead to an under‐ or overestimated number of SNPs and/or to incorrectly called genotypes. Using the Atlantic mackerel (Scomber scombrus L.) and a close relative, the Atlantic chub mackerel (Scomber colias), as case study, here we explore the sensitivity of population structure inferences to two crucial aspects in RAD‐seq data analysis: the maximum number of mismatches allowed to merge reads into a locus and the relatedness of the individuals used for genotype calling and SNP selection. Our study resolves the population structure of the Atlantic mackerel, but, most importantly, provides insights into the effects of alternative RAD‐seq data analysis strategies on population structure inferences that are directly applicable to other species.

Current methods for monitoring marine fish (including bony fishes and elasmobranchs) diversity mostly rely on trawling surveys, which are invasive, costly, and time‐consuming. Moreover, these methods are selective, targeting a subset of species at the time, and can be inaccessible to certain areas. Here, we used environmental DNA (eDNA), the DNA present in the water column as part of shed cells, tissues, or mucus, to provide comprehensive information about fish diversity in a large marine area. Further, eDNA results were compared to the fish diversity obtained in pelagic trawls. A total of 44 5 L‐water samples were collected onboard a wide‐scale oceanographic survey covering about 120,000 square kilometers in Northeast Atlantic Ocean. A short region of the 12S rRNA gene was amplified and sequenced through metabarcoding generating almost 3.5 million quality‐filtered reads. Trawl and eDNA samples resulted in the same most abundant species (European anchovy, European pilchard, Atlantic mackerel, and blue whiting), but eDNA metabarcoding resulted in more detected bony fish and elasmobranch species (116) than trawling (16). Although an overall correlation between fishes biomass and number of reads was observed, some species deviated from the common trend, which could be explained by inherent biases of each of the methods. Species distribution patterns inferred from eDNA metabarcoding data coincided with current ecological knowledge of the species, suggesting that eDNA has the potential to draw sound ecological conclusions that can contribute to fish surveillance programs. Our results support eDNA metabarcoding for broad‐scale marine fish diversity monitoring in the context of Directives such as the Common Fisheries Policy or the Marine Strategy Framework Directive.

Autonomous Reef Monitoring Structures (ARMS) have been applied worldwide to characterize the critical yet frequently overlooked biodiversity patterns of marine benthic organisms. In order to disentangle the relevance of environmental factors in benthic patterns, here, through standardized metabarcoding protocols, we analyse sessile and mobile (<2 mm) organisms collected using ARMS deployed across six regions with different environmental conditions (3 sites × 3 replicates per region): Baltic, Western Mediterranean, Adriatic, Black and Red Seas, and the Bay of Biscay. A total of 27,473 Amplicon Sequence Variants (ASVs) were observed ranging from 1,404 in the Black Sea to 9,958 in the Red Sea. No ASVs were shared among all regions. The highest number of shared ASVs was between the Western Mediterranean and the Adriatic Sea (116) and Bay of Biscay (115). Relatively high numbers of ASVs (103), mostly associated with the genus Amphibalanus, were also shared between the lower salinity seas (Baltic and Black Seas). We found that compositional differences in spatial patterns of rocky-shore benthos are determined slightly more by dispersal limitation than environmental filtering. Dispersal limitation was similar between sessile and mobile groups, while the sessile group had a larger environmental niche | 4883

Routine monitoring of benthic biodiversity is critical for managing and understanding the anthropogenic impacts on marine, transitional and freshwater ecosystems.However, traditional reliance on morphological identification generally makes it costprohibitive to increase the scale of monitoring programmes. Metabarcoding of environmental DNA has clear potential to overcome many of the problems associated with traditional monitoring, with prokaryotes and other microorganisms showing particular promise as bioindicators. However, due to the limited knowledge regarding the ecological roles and responses of environmental microorganisms to different types of pressure, the use of de novo approaches is necessary. Here, we use two such approaches for the prediction of multiple impacts present in estuaries and coastal areas of the Bay of Biscay based on microbial communities. The first (Random Forests) is a machine learning method while the second (Threshold Indicator Taxa Analysis and quantile regression splines) is based on de novo identification of bioindicators. Our results show that both methods overlap considerably in the indicator taxa identified, but less for sequence variants. Both methods also perform well in spite of the complexity of the studied ecosystem, providing predictive models with strong correlation to reference values and fair to good agreement with ecological status groups. The ability to predict several specific types of pressure is especially appealing. The cross-validated models and biotic indices developed can be directly applied to predict the environmental status of estuaries in the same geographical region, although more work is needed to evaluate and improve them for use in new regions or habitats.

Metabarcoding is an accurate and cost-effective technique that allows for simultaneous taxonomic identification of multiple environmental samples. Application of this technique to marine benthic macroinvertebrate biodiversity assessment for biomonitoring purposes requires standardization of laboratory and data analysis procedures. In this context, protocols for creation and sequencing of amplicon libraries and their related bioinformatics analysis have been recently published. However, a standardized protocol describing all previous steps (i.e., processing and manipulation of environmental samples for macroinvertebrate community characterization) is lacking. Here, we provide detailed procedures for benthic environmental sample collection, processing, enrichment for macroinvertebrates, homogenization, and subsequent DNA extraction for metabarcoding analysis. Since this is the first protocol of this kind, it should be of use to any researcher in this field, having the potential for improvement.

0Current methods for monitoring marine fish diversity mostly rely on trawling surveys, 1 1 which are invasive, costly and time-consuming. Moreover, these methods are selective,

The deep sea provides global vital functions such as sequestration of carbon from the atmosphere. The increased anthropogenic pressures and interest in expanding deep-sea fisheries make this pristine ecosystem particularly vulnerable, whose conservation largely depends on rapid knowledge acquisition. In view of the limitations of traditional methods to explore the biodiversity of this vast ecosystem, the analysis of traces of macroorganismal DNA released into the water column arises as a cost-effective, noninvasive alternative. Yet, the success of this approach requires understanding of the stratification of DNA traces in the ocean. This study provides evidence that fish DNA traces can be used to establish depth-specific fish diversity and abundance throughout the water column, opening a promising avenue for gathering knowledge about the deep-sea ecosystem.Establishing the foundations for a sustainable use of deep-sea resources relies on increasing knowledge on this inaccessible ecosystem, which is challenging with traditional methods. The analysis of environmental DNA (eDNA) emerges as an alternative, but it has been scarcely applied to deep-sea fish. Here, we have analyzed the fish eDNA contained in oceanic vertical profile samples (up to 2000 m depth) collected throughout the continental slope of the Bay of Biscay. We detected 52 different fish species, of which 25 were classified as deep-sea fish. We found an increase of deep-sea fish richness and abundance with depth, and that eDNA reflects daynight community patterns and species-specific vertical distributions that are consistent with the known diel migratory behavior of many mesopelagic fishes. These findings highlight the potential of eDNA to improve knowledge on the fish species inhabiting the dark ocean before this still pristine ecosystem is further exploited.

Susceptibility to develop nonalcoholic fatty liver disease (NAFLD) has genetic bases, but the associated variants are uncertain. The aim of the present study was to identify genetic variants that could help to prognose and further understand the genetics and development of NAFLD. Allele frequencies of 3,072 single-nucleotide polymorphisms (SNPs) in 92 genes were characterized in 69 NAFLD patients and 217 healthy individuals. The markers that showed significant allele-frequency differences in the pilot groups were subsequently studied in 451 NAFLD patients and 304 healthy controls. Besides this, 4,414 type 2 diabetes mellitus (T2DM) cases and 4,567 controls were genotyped. Liver expression of the associated gene was measured and the effect of its potential role was studied by silencing the gene in vitro. Whole genome expression, oxidative stress (OS), and the consequences of oleic acid (OA)-enriched medium on lipid accumulation in siSLC2A1-THLE2 cells were studied by gene-expression analysis, dihydroethidium staining, BODIPY, and quantification of intracellular triglyceride content, respectively. Several SNPs of SLC2A1 (solute carrier family 2 [facilitated glucose transporter] member 1) showed association with NAFLD, but not with T2DM, being the haplotype containing the minor allele of SLC2A1 sequence related to the susceptibility to develop NAFLD. Gene-expression analysis demonstrated a significant down-regulation of SLC2A1 in NAFLD livers. Enrichment functional analyses