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Understanding why certain host species harbor more parasites is an important question in parasite and fish ecology. Parasite infection among sympatric species may integrate various processes affecting parasite assembly, including the species-specific ecology and the success of invaders. We focused on spatial, environmental, and host-related determinants of parasite assembly in three riverine fish species: the native three-spined stickleback and stone loach, and the invasive topmouth gudgeon. Parasite community structure differed significantly between the three host species. Three-spined stickleback harbored the most ectoparasites. Host density and nutrients were the strongest predictors of its parasite communities. Topmouth gudgeon harbored the lowest number of parasites, both in terms of abundance and species richness. None of the parasites identified originated from its expanded range, suggesting that enemy release occurred during invasion. Temperature and host density predicted parasite assemblages of topmouth gudgeon. Stone loach hosted the most endoparasites, likely resulting from its varied diet, benthic lifestyle, and larger size. Additionally, host size and condition were positively correlated with parasite infection, which was similar among the three host species. The results suggest that host-related factors have a similar effect among host species, while the importance of environmental and spatial factors differs according to host ecology.

We present a comparative genetic analysis of the quantitative trait loci underlying resistance to warm water columnaris disease in 2 farmed rainbow trout (Oncorhynchus mykiss) populations. We provide evidence for the conservation of a major quantitative trait loci on Omy03, and the putative role played by a chromosomal rearrangement on Omy05. A total of 3,962 individuals from the 2 populations experienced a natural Flavobacterium columnare outbreak. Data for 25,823 genome-wide SNPs were generated for both cases (fatalities) and controls (survivors). FST and pairwise additive genetic relationships suggest that, despite being currently kept as separate broodstocks, the 2 populations are closely related. Association analyses identified a major quantitative trait loci on chromosome Omy03 and a second smaller quantitative trait loci on Omy05. Quantitative trait loci on Omy03 consistently explained 3–11% of genetic variation in both populations, whereas quantitative trait loci on Omy05 showed different degree of association across populations and sexes. The quantitative trait loci on Omy05 was found within a naturally occurring, 54.84 cM long inversion which is easy to tag due to a strong linkage disequilibrium between the 375 tagging SNPs. The ancestral haplotype on Omy05 was associated with decreased mortality. Genetic correlation between mortality in the 2 populations was estimated at 0.64, implying that the genetic basis of resistance is partly similar in the 2 populations. Our quantitative trait loci validation identifies markers that can be potentially used to complement breeding value evaluations to increase resistance against columnaris disease, and help to mitigate effects of climate change on aquaculture.

The European Union adopted the Water Framework Directive (WFD) in the year 2000 to tackle the rapid degradation of freshwater systems. However, biological, hydromorphological, and physico-chemical water quality targets are currently not met, and identifying successful policy implementation and management actions is of key importance. We built a joint species distribution model for riverine fish in Flanders (Belgium) to better understand the response of fish communities to current environmental policy goals. Environmental covariates included physico-chemical variables and hydromorphological quality indices, while waterway distances accounted for spatial effects. We detected strong effects of physico-chemistry on fish species’ distributions. Evaluation of fish community responses to simulated policy scenarios revealed that targeting a ‘good’ status, following the WFD, increases average species richness with a fraction of species (0.13–0.69 change in accumulated occurrence probabilities). Targeting a ‘very good’ status, however, predicted an increase of 0.17–1.38 in average species richness. These simulations indicated that riverbed quality, nitrogen, and conductivity levels should be the focal point of policy. However, the weak response of species to a ‘good’ quality together with the complexity of nutrient-associated problems, suggest a challenging future for river restoration in Flanders.

Dogs are of increasing interest as models for human diseases, and many canine population-association studies are beginning to emerge. The choice of breeds for such studies should be informed by a knowledge of factors such as inbreeding, genetic diversity, and population structure, which are likely to depend on breed-specific selective breeding patterns. To address the lack of such studies we have exploited one of the world's most extensive resources for canine population-genetics studies: the United Kingdom (UK) Kennel Club registration database. We chose 10 representative breeds and analyzed their pedigrees since electronic records were established around 1970, corresponding to about eight generations before present. We find extremely inbred dogs in each breed except the greyhound and estimate an inbreeding effective population size between 40 and 80 for all but 2 breeds. For all but 3 breeds, >90% of unique genetic variants are lost over six generations, indicating a dramatic effect of breeding patterns on genetic diversity. We introduce a novel index Ψ for measuring population structure directly from the pedigree and use it to identify subpopulations in several breeds. As well as informing the design of canine population genetics studies, our results have implications for breeding practices to enhance canine welfare.

Background Clupeid fisheries in Lake Tanganyika (East Africa) provide food for millions of people in one of the world’s poorest regions. Due to climate change and overfishing, the clupeid stocks of Lake Tanganyika are declining. We investigate the population structure of the Lake Tanganyika sprat Stolothrissa tanganicae, using for the first time a genomic approach on this species. This is an important step towards knowing if the species should be managed separately or as a single stock. Population structure is important for fisheries management, yet understudied for many African freshwater species. We hypothesize that distinct stocks of S. tanganicae could be present due to the large size of the lake (isolation by distance), limnological variation (adaptive evolution), or past separation of the lake (historical subdivision). On the other hand, high mobility of the species and lack of obvious migration barriers might have resulted in a homogenous population. Results We performed a population genetic study on wild-caught S. tanganicae through a combination of mitochondrial genotyping (96 individuals) and RAD sequencing (83 individuals) . Samples were collected at five locations along a north-south axis of Lake Tanganyika. The mtDNA data had low global FST and, visualised in a haplotype network, did not show phylogeographic structure. RAD sequencing yielded a panel of 3504 SNPs, with low genetic differentiation (F ST  = 0.0054; 95% CI: 0.0046–0.0066). PCoA, fineRADstructure and global F ST suggest a near-panmictic population. Two distinct groups are apparent in these analyses (F ST  = 0.1338 95% CI: 0.1239,0.1445), which do not correspond to sampling locations. Autocorrelation analysis showed a slight increase in genetic difference with increasing distance. No outlier loci were detected in the RADseq data. Conclusion Our results show at most very weak geographical structuring of the stock and do not provide evidence for genetic adaptation to historical or environmental differences over a north-south axis. Based on these results, we advise to manage the stock as one population, integrating one management strategy over the four riparian countries. These results are a first comprehensive study on the population structure of these important fisheries target species, and can guide fisheries management.

Anthropogenic stressors, such as pollutants, act as selective factors that can leave measurable changes in allele frequencies in the genome. Metals are of particular concern among pollutants, because of interference with vital biological pathways. We use the three-spined stickleback as a model for adaptation to mercury pollution in natural populations. We collected sticklebacks from 21 locations in Flanders (Belgium), measured the accumulated levels of mercury in the skeletal muscle tissue, and genotyped the fish by sequencing (GBS). The spread of muscle mercury content across locations was considerable, ranging from 21.5 to 327 ng/g dry weight (DW). We then conducted a genome-wide association study (GWAS) between 28,450 single nucleotide polymorphisms (SNPs) and the accumulated levels of mercury, using different approaches. Based on a linear mixed model analysis, the GWAS yielded multiple hits with a single top hit on Chromosome 4, with eight more SNPs suggestive of association. A second approach, a latent factor mixed model analysis, highlighted one single SNP on Chromosome 11. Finally, an outlier test identified one additional SNP on Chromosome 4 that appeared under selection. Out of all ten SNPs we identified as associated with mercury in muscle, three SNPs all located on Chromosome 4 and positioned within a 2.5 kb distance of an annotated gene. Based on these results and the genome coverage of our SNPs, we conclude that the selective effect of mercury pollution in Flanders causes a significant association with at least one locus on Chromosome 4 in three-spined stickleback.

Uncertainty hampers innovative mixed‐fisheries management by the scales at which connectivity dynamics are relevant to management objectives. The spatial scale of sustainable stock management is species‐specific and depends on ecology, life history and population connectivity. One valuable approach to understand these spatial scales is to determine to what extent population genetic structure correlates with the oceanographic environment. Here, we compare the level of genetic connectivity in three codistributed and commercially exploited demersal flatfish species living in the North East Atlantic Ocean. Population genetic structure was analysed based on 14, 14 and 10 neutral DNA microsatellite markers for turbot, brill and sole, respectively. We then used redundancy analysis (RDA) to attribute the genetic variation to spatial (geographical location), temporal (sampling year) and oceanographic (water column characteristics) components. The genetic structure of turbot was composed of three clusters and correlated with variation in the depth of the pycnocline, in addition to spatial factors. The genetic structure of brill was homogenous, but correlated with average annual stratification and spatial factors. In sole, the genetic structure was composed of three clusters, but was only linked to a temporal factor. We explored whether the management of data poor commercial fisheries, such as in brill and turbot, might benefit from population‐specific information. We conclude that the management of fish stocks has to consider species‐specific genetic structures and may benefit from the documentation of the genetic seascape and life‐history traits.

The genome-wide association study (GWAS) approach has discovered hundreds of genetic variants associated with diseases and quantitative traits. However, despite clinical overlap and statistical correlation between many phenotypes, GWAS are generally performed one-phenotype-at-a-time. Here we compare the performance of modelling multiple phenotypes jointly with that of the standard univariate approach. We introduce a new method and software, MultiPhen, that models multiple phenotypes simultaneously in a fast and interpretable way. By performing ordinal regression, MultiPhen tests the linear combination of phenotypes most associated with the genotypes at each SNP, and thus potentially captures effects hidden to single phenotype GWAS. We demonstrate via simulation that this approach provides a dramatic increase in power in many scenarios. There is a boost in power for variants that affect multiple phenotypes and for those that affect only one phenotype. While other multivariate methods have similar power gains, we describe several benefits of MultiPhen over these. In particular, we demonstrate that other multivariate methods that assume the genotypes are normally distributed, such as canonical correlation analysis (CCA) and MANOVA, can have highly inflated type-1 error rates when testing case-control or non-normal continuous phenotypes, while MultiPhen produces no such inflation. To test the performance of MultiPhen on real data we applied it to lipid traits in the Northern Finland Birth Cohort 1966 (NFBC1966). In these data MultiPhen discovers 21% more independent SNPs with known associations than the standard univariate GWAS approach, while applying MultiPhen in addition to the standard approach provides 37% increased discovery. The most associated linear combinations of the lipids estimated by MultiPhen at the leading SNPs accurately reflect the Friedewald Formula, suggesting that MultiPhen could be used to refine the definition of existing phenotypes or uncover novel heritable phenotypes.

Throughout all stages of fish conservation and aquaculture development, genetic and genomic approaches can be leveraged to enhance understanding of the diversity and complexity of these organisms, including the linkage between phenotype and genotype, and their adaptive and breeding potential. These approaches can inform processes ranging from the initial collection of wild broodstock to the ongoing use of genomic selection on domesticated lines. Due to the diversity in cultured fish species, small and medium enterprises (SMEs) commonly explore new species for culture, or work with species within a narrow regional conservation or commercial focus. These enterprises face obstacles in utilising genetic and genomic approaches due to development and implementation costs, specialised skill set requirements, and infrastructure and labour limitations; yet the benefits often outweigh these challenges. Choosing the best molecular genetic or genomic tools depends on programme goals and species, but small and medium enterprises may miss opportunities to acquire more information through their current approaches, or not realise what may be gained through modest investments in genomic tools. To provide better insight and promote discussion and collaboration between culturists and genomic practitioners, we define and describe five States of development and application of genetic and genomic tools frequently observed in aquaculture and conservation breeding programs. We characterise these tools, their general applications, and how current technologies allow programs to advance to higher States without following a sequential progression, a concept we refer to as “State skipping”. This document outlines the available molecular genetic and genomic tools, but does not cover animal breeding or the science behind it. Similarly, bioeconomic models are not included, although relative economic costs and benefits are highlighted. The technical considerations and limitations of various approaches are reviewed, along with available resources for those seeking further support in exploring genetic and genomic tools in breeding programmes.

Habitat fragmentation impacts the distribution of genetic diversity and population genetic structure. Therefore, protecting the evolutionary potential of species, especially in the context of the current rate of human‐induced environmental change, is an important goal. In riverine ecosystems, migration barriers affect the genetic structure of native species, while also influencing the spread of invasive species. In this study, we compare genetic patterns of two native and one highly invasive riverine fish species in a Belgian river basin, namely the native three‐spined stickleback (Gasterosteus aculeatus) and stone loach (Barbatula barbatula), and the non‐native and invasive topmouth gudgeon (Pseudorasbora parva). We aimed to characterize both natural and anthropogenic determinants of genetic diversity and population genetic connectivity. Genetic diversity was highest in topmouth gudgeon, followed by stone loach and three‐spined stickleback. The correlation between downstream distance and genetic diversity, a pattern often observed in riverine systems, was only marginally significant in stone loach and three‐spined stickleback, while genetic diversity strongly declined with increasing number of barriers in topmouth gudgeon. An Isolation‐By‐Distance pattern characterizes the population genetic structure of each species. Population differentiation was only associated with migration barriers in the invasive topmouth gudgeon, while genetic composition of all species seemed at least partially determined by the presence of migration barriers. Among the six barrier types considered (watermills, sluices, tunnels, weirs, riverbed obstructions, and others), the presence of watermills was the strongest driver of genetic structure and composition. Our results indicate that conservation and restoration actions, focusing on conserving genetic patterns, cannot be generalized across species. Moreover, measures might target either on restoring connectivity, while risking a rapid spread of the invasive topmouth gudgeon, or not restoring connectivity, while risking native species extinction in upstream populations.