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In recent years, the analysis of environmental DNA (eDNA) has significantly improved, allowing for high-resolution species identification and possible biomass quantification from water samples. Fisheries management typically requires monitoring of catches, including precise information about bycatch quantities to make sound assessments of exploitation rates. Bycatch assessment is particularly challenging in large catches (>500 T), and the current practice of visual assessment of subsampled catches is time-consuming, requires extensive labor, and often has low precision. We explored the feasibility for applying eDNA-based methods for studying catch composition using the pelagic North Sea herring fishery with bycatch of mackerel as a case. First, we experimentally simulate a series of catches using a range of herring and mackerel weight proportions to establish relationships under real fisheries scenarios. The relationship is subsequently used to estimate the biomass of mackerel bycatch from eDNA from three herring catches, by sampling and comparing processing water both onboard ships and at the processing factory. All samples are analyzed using species-specific quantitative PCR (qPCR). The experiments reveled a strong correlation between DNA and weight fractions characterized by a constant overrepresentation of mackerel DNA compared to expected mackerel weight. We found that eDNA-based and visual methods applied to the same landing reflect the within catch variability in species composition alike, however, the methods can show disparity in total estimates of mackerel biomass. Accounting for haul mixing within total landed catches increases the precision of the factory and ship eDNA-based estimates for the same catch. We show that eDNA-based bycatch estimates provide coherent quantitative data, and likely improve quality and reduce costs of collecting fisheries-dependent data and thereby contribute to securing sustainable fisheries.

Atlantic cod is a keystone species that remains among the most economically important demersal fish in the North Atlantic. Throughout its distribution range, Atlantic cod is composed of populations with varying environmental preferences and migratory propensities. This life-history variation is likely to have contributed to the niche width and large population sizes of Atlantic cod, and its relative resilience to environmental change and exploitation. The Icelandic cod stock is currently managed as a single unit, but early research indicates population variation by depth and temperature and distinct offshore and inshore spawning components. Pelagic 0-group juveniles from different spawning grounds coexist in nursery areas around Iceland, but their genetic composition or habitat partitioning had not been examined post benthic settlement. In the current study we examine the genetic composition of Atlantic cod juvenile aggregations at nearshore nursery grounds in NW-Iceland and report distinct segregation by the depth of offshore and inshore juvenile cod. The physiological mechanism of this segregation is not known, but the pattern demonstrates the need to consider population structure at nursery grounds in the application of marine spatial planning and other area-based conservation tools.

Mixed-stock fisheries pose a challenge for fisheries management recommendations and management, as mixed stocks can lead to unintentional over- or under-exploitation of stocks, with both short- and long-term biological and economic consequences. This study demonstrates practical application and implementation of year-round high-resolution genetic stock monitoring in management of mixed Atlantic cod (Gadus morhua) stocks in western Greenland. Using a panel of 96 high resolution gene-associated SNPs, we identified the stock of origin for four cod stocks in the two major inshore mixed-stock fisheries. Contribution of individual stocks was quantified to identify if fjord sections, times of year, and fish size, would allow a “clean fishery” with a minimal contribution of the depleted West Greenland Offshore (WGO) population. High level of mixing was identified with 50% of inshore catches originating from the inshore stock, 20% from the East Greenland/Iceland offshore stock, and 30% from the WGO stock. Although some spatiotemporal variation of stock proportions was identified, a practice allowing exclusively fishing a specific stock was not possible. Accordingly, we demonstrate the need to allocate catches at the biological stock level and show that application of high-resolution genetics is a reliable and necessary tool.

Targeted sequencing is an increasingly popular Next Generation Sequencing (NGS) approach for studying populations that involves focusing sequencing efforts on specific parts of the genome of a species of interest. Methodologies and tools for designing targeted baits are scarce but in high demand. Here, we present specific guidelines and considerations for designing capture sequencing experiments for population genetics for both neutral genomic regions and regions subject to selection. We describe the bait design process for three diverse fish species: Atlantic salmon, Atlantic cod and tiger shark, which was carried out in our research group, and provide an evaluation of the performance of our approach across both historical and modern samples. The workflow used for designing these three bait sets has been implemented in the R-package supeRbaits, which encompasses our considerations and guidelines for bait design for the benefit of researchers and practitioners. The supeRbaits R-package is user-friendly and versatile. It is written in C++ and implemented in R. supeRbaits and its manual are available from Github: https://github.com/BelenJM/supeRbaits.

The Atlantic herring Clupea harengus L has a vast geographical distribution and a complex population structure with a few very large migratory units and many small local populations. Each population has its own spawning ground and/or time, thereby maintaining their genetic integrity. Several herring populations migrate between common feeding grounds and over-wintering areas resulting in frequent mixing of populations. Thus, many herring fisheries are based on mixed populations of different demographic status. In order to avoid overexploitation of weak populations and to conserve biodiversity, understanding the population structure and population mixing is important for maintaining biologically sustainable herring fisheries. The aim of this study was to investigate the genetic population structure of herring in the Faroese and surrounding waters, and to develop genetic markers for distinguishing between four herring management units (often called stocks), namely the Norwegian spring-spawning herring (NSSH), Icelandic summer-spawning herring (ISSH), North Sea autumn-spawning herring (NSAH), and Faroese autumn-spawning herring (FASH). Herring from the four stocks were sequenced at low coverage, and single nucleotide polymorphisms (SNPs) were called and used for population structure analysis and individual assignment. An ancestry-informative SNP panel with 118 SNPs was developed and tested on 240 individuals. The results showed that all four stocks appeared to be genetically differentiated populations, but at lower levels of differentiation between FASH and ISSH than the other two populations. Overall assignment rate with the SNP panel was 80.7%, and agreement between the genetic and traditional visual assignment was 75.5%. The NSAH and NSSH samples had the highest assignment rate (100% and 98.3%, respectively) and highest agreement between traditional and genetic assignment methods (96.6% and 94.9%, respectively). The FASH and ISSH samples had substantially lowe

The survival of Atlantic salmon (Salmo salar), an increasingly rare anadromous species, has declined dramatically during its marine phase, with disproportionate impacts on the poorly understood early post-smolt period. Logistical constraints on collecting oceanic data to inform this issue pose a formidable obstacle. To advance understanding of post-smolt distributional ecology in the North-east Atlantic, a comprehensive analysis of existing information was undertaken. Data were synthesized from 385 marine cruises, 10,202 individual trawls, and 9,269 captured post-smolts, spanning three decades and ~4.75 million km2 of ocean, with 3,423 individuals genetically assigned to regional phylogeographic origin. The findings confirm major migrational post-smolt aggregations on the continental shelf-edge off Ireland, Scotland and Norway, and an important marine foraging area in the Norwegian Sea. Genetic analysis shows that aggregational stock composition does not simply reflect distance to natal rivers, with northern phylogeographic stock groups significantly under-represented in sampled high-seas aggregations. It identifies a key foraging habitat for southern European post-smolts located in international waters immediately west of the Vøring Plateau escarpment, potentially exposing them to a high by-catch mortality from extra-territorial pelagic fisheries. Evidence of the differential distribution of regional stocks points to fundamental differences in their migration behaviours and may lead to inter-stock variation in responses to environmental change and marine survival. The study shows that understanding of post-smolt marine ecology, as regards to stock-specific variations in habitat utilization, biological performance and exposure to mortality factors, can be significantly advanced by data integration across studies and exploiting genetic approaches.

The identification of the genetic basis of domestication in fish species is of timely importance for the aquaculture industry in order to increase productivity, quality, and the welfare of farmed fish. The goal of this study is to investigate the largely unknown aquaculture-induced evolution in gilthead seabream, which is one of the most important farmed fish in the Mediterranean region. We used a panel of 1159 genome-wide SNPs, and genotyped 956 fish from 23 wild populations of Mediterranean-wide distribution and 362 farmed fish from five Greek hatcheries. We assessed the genetic diversity of the sampled populations and contrasted the results of four different approaches of outlier detection methods. We recognized one very strong candidate and two good candidate SNPs with evidence for aquaculture-induced evolution in gilthead seabream. The annotation of these SNPs revealed neighboring genes with biological roles from stress tolerance and disease resistance to sexual maturation that may explain our observations. In conclusion, we demonstrate that the genome of gilthead seabream, despite the fact that the species is often suggested to be in the early stages of the domestication process, shows evidence of aquaculture-induced evolution. We report on a list of genes that may explain our observations and that may be investigated further. We anticipate that our findings will stimulate additional research with the use of SNP panels of higher density that can elucidate the genomic architecture of domestication in this species of high aquacultural interest.

Human-mediated transport creates secondary contacts between genetically differentiated lineages, bringing new opportunities for gene exchange. When similar introductions occur in different places, they provide informally replicated experiments for studying hybridisation. We here examined 4,279 Mytilus mussels, sampled in Europe and genotyped with 77 ancestry-informative markers. We identified a type of introduced mussels, called "dock mussels," associated with port habitats and displaying a particular genetic signal of admixture between M. edulis and the Mediterranean lineage of M. galloprovincialis. These mussels exhibit similarities in their ancestry compositions, regardless of the local native genetic backgrounds and the distance separating colonised ports. We observed fine-scale genetic shifts at the port entrance, at scales below natural dispersal distance. Such sharp clines do not fit with migration-selection tension zone models, and instead suggest habitat choice and early-stage adaptation to the port environment, possibly coupled with connectivity barriers. Variations in the spread and admixture patterns of dock mussels seem to be influenced by the local native genetic backgrounds encountered. We next examined departures from the average admixture rate at different loci, and compared human-mediated admixture events, to naturally admixed populations and experimental crosses. When the same M. galloprovincialis background was involved, positive correlations in the departures of loci across locations were found; but when different backgrounds were involved, no or negative correlations were observed. While some observed positive correlations might be best explained by a shared history and saltatory colonisation, others are likely produced by parallel selective events. Altogether, genome-wide effect of admixture seems repeatable and more dependent on genetic background than environmental context. Our results pave the way towards further genomic analyses of admixtu

Fisheries enforcement relies on visual catch identification and quantification at sea or when landed. Silage (fish dissolved in acid) and fish blocks (block frozen fish) are promising methods for on-board processing and storage of low-value catches. We examined the use of nondestructive sampling and two DNA-based methods, quantitative PCR (qPCR) and metabarcoding, to assess species composition and relative abundance in industrial grade experimental silage and fish blocks. We demonstrate the ability to identify and quantify DNA from fish species in both products. qPCR analysis of small silage samples collected over 21 days detected all target control species. DNA from one species (Atlantic wolffish) was consistently overrepresented while, for three species of gadoids (Atlantic cod, haddock and whiting), the DNA content matched input tissue proportions with high accuracy. qPCR and metabarcoding of fish blocks, sampled as run-off water and exterior swabs, provided consistent species detection, with the highest variance observed in quantification from swab samples. Our analysis shows that DNA-based methods have significant potential as a tool for species identification and quantification of complex on-board-processed seafood products and are readily applicable to taxonomically and morphologically similar fish. There is, however, a need for establishing DNA/weight calibration factors for primary fisheries species.

Genetic data have great potential for improving fisheries management by identifying the fundamental management units—that is, the biological populations—and their mixing. However, so far, the number of practical cases of marine fisheries management using genetics has been limited. Here, we used Atlantic cod in the Baltic Sea to demonstrate the applicability of genetics to a complex management scenario involving mixing of two genetically divergent populations. Specifically, we addressed several assumptions used in the current assessment of the two populations. Through analysis of 483 single nucleotide polymorphisms (SNPs) distributed across the Atlantic cod genome, we confirmed that a model of mechanical mixing, rather than hybridization and introgression, best explained the pattern of genetic differentiation. Thus, the fishery is best monitored as a mixed-stock fishery. Next, we developed a targeted panel of 39 SNPs with high statistical power for identifying population of origin and analyzed more than 2,000 tissue samples collected between 2011 and 2015 as well as 260 otoliths collected in 2003/2004. These data provided high spatial resolution and allowed us to investigate geographical trends in mixing, to compare patterns for different life stages and to investigate temporal trends in mixing. We found similar geographical trends for the two time points represented by tissue and otolith samples and that a recently implemented geographical management separation of the two populations provided a relatively close match to their distributions. In contrast to the current assumption, we found that patterns of mixing differed between juveniles and adults, a signal likely linked to the different reproductive dynamics of the two populations. Collectively, our data confirm that genetics is an operational tool for complex fisheries management applications. We recommend focussing on developing population assessment models and fisheries management frameworks to capitalize fully

Unraveling adaptive genetic variation represents, in addition to the estimate of population demographic parameters, a cornerstone for the management of aquatic natural living resources, which, in turn, represent the raw material for breeding programs. The turbot (Scophthalmus maximus) is a marine flatfish of high commercial value living on the European continental shelf. While wild populations are declining, aquaculture is flourishing in southern Europe. We evaluated the genetic structure of turbot throughout its natural distribution range (672 individuals; 20 populations) by analyzing allele frequency data from 755 single nucleotide polymorphism discovered and genotyped by double‐digest RAD sequencing. The species was structured into four main regions: Baltic Sea, Atlantic Ocean, Adriatic Sea, and Black Sea, with subtle differentiation apparent at the distribution margins of the Atlantic region. Genetic diversity and effective population size estimates were highest in the Atlantic populations, the area of greatest occurrence, while turbot from other regions showed lower levels, reflecting geographical isolation and reduced abundance. Divergent selection was detected within and between the Atlantic Ocean and Baltic Sea regions, and also when comparing these two regions with the Black Sea. Evidence of parallel evolution was detected between the two low salinity regions, the Baltic and Black seas. Correlation between genetic and environmental variation indicated that temperature and salinity were probably the main environmental drivers of selection. Mining around the four genomic regions consistently inferred to be under selection identified candidate genes related to osmoregulation, growth, and resistance to diseases. The new insights are useful for the management of turbot fisheries and aquaculture by providing the baseline for evaluating the consequences of turbot releases from restocking and farming.

The development of Genotyping-By-Sequencing (GBS) technologies enables cost-effective analysis of large numbers of Single Nucleotide Polymorphisms (SNPs), especially in “non-model” species. Nevertheless, as such technologies enter a mature phase, biases and errors inherent to GBS are becoming evident. Here, we evaluated the performance of double digest Restriction enzyme Associated DNA (ddRAD) sequencing in SNP genotyping studies including high number of samples. Datasets of sequence data were generated from three marine teleost species (>5500 samples, >2.5 × 1012 bases in total), using a standardized protocol. A common bioinformatics pipeline based on STACKS was established, with and without the use of a reference genome. We performed analyses throughout the production and analysis of ddRAD data in order to explore (i) the loss of information due to heterogeneous raw read number across samples; (ii) the discrepancy between expected and observed tag length and coverage; (iii) the performances of reference based vs. de novo approaches; (iv) the sources of potential genotyping errors of the library preparation/bioinformatics protocol, by comparing technical replicates. Our results showed use of a reference genome and a posteriori genotype correction improved genotyping precision. Individual read coverage was a key variable for reproducibility; variance in sequencing depth between loci in the same individual was also identified as an important factor and found to correlate to tag length. A comparison of downstream analysis carried out with ddRAD vs single SNP allele specific assay genotypes provided information about the levels of genotyping imprecision that can have a significant impact on allele frequency estimations and population assignment. The results and insights presented here will help to select and improve approaches to the analysis of large datasets based on RAD-like methodologies

The development of Genotyping-By-Sequencing (GBS) technologies enables cost-effective analysis of large numbers of Single Nucleotide Polymorphisms (SNPs), especially in "non-model" species. Nevertheless, as such technologies enter a mature phase, biases and errors inherent to GBS are becoming evident. Here, we evaluated the performance of double digest Restriction enzyme Associated DNA (ddRAD) sequencing in SNP genotyping studies including high number of samples. Datasets of sequence data were generated from three marine teleost species (>5500 samples, >2.5 × 1012 bases in total), using a standardized protocol. A common bioinformatics pipeline based on STACKS was established, with and without the use of a reference genome. We performed analyses throughout the production and analysis of ddRAD data in order to explore (i) the loss of information due to heterogeneous raw read number across samples; (ii) the discrepancy between expected and observed tag length and coverage; (iii) the performances of reference based vs. de novo approaches; (iv) the sources of potential genotyping errors of the library preparation/bioinformatics protocol, by comparing technical replicates. Our results showed use of a reference genome and a posteriori genotype correction improved genotyping precision. Individual read coverage was a key variable for reproducibility; variance in sequencing depth between loci in the same individual was also identified as an important factor and found to correlate to tag length. A comparison of downstream analysis carried out with ddRAD vs single SNP allele specific assay genotypes provided information about the levels of genotyping imprecision that can have a significant impact on allele frequency estimations and population assignment. The results and insights presented here will help to select and improve approaches to the analysis of large datasets based on RAD-like methodologies.

Unraveling adaptive genetic variation represents, in addition to the estimate of population demographic parameters, a cornerstone for the management of aquatic natural living resources, which, in turn, represent the raw material for breeding programs. The turbot (Scophthalmus maximus) is a marine flatfish of high commercial value living on the European continental shelf. While wild populations are declining, aquaculture is flourishing in southern Europe. We evaluated the genetic structure of turbot throughout its natural distribution range (672 individuals; 20 populations) by analyzing allele frequency data from 755 single nucleotide polymorphism discovered and genotyped by double-digest RAD sequencing. The species was structured into four main regions: Baltic Sea, Atlantic Ocean, Adriatic Sea, and Black Sea, with subtle differentiation apparent at the distribution margins of the Atlantic region. Genetic diversity and effective population size estimates were highest in the Atlantic populations, the area of greatest occurrence, while turbot from other regions showed lower levels, reflecting geographical isolation and reduced abundance. Divergent selection was detected within and between the Atlantic Ocean and Baltic Sea regions, and also when comparing these two regions with the Black Sea. Evidence of parallel evolution was detected between the two low salinity regions, the Baltic and Black seas. Correlation between genetic and environmental variation indicated that temperature and salinity were probably the main environmental drivers of selection. Mining around the four genomic regions consistently inferred to be under selection identified candidate genes related to osmoregulation, growth, and resistance to diseases. The new insights are useful for the management of turbot fisheries and aquaculture by providing the baseline for evaluating the consequences of turbot releases from restocking and farming.