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Aquaculture is the fastest-growing farmed food sector and will soon become the primary source of fish and shellfish for human diets. In contrast to crop and livestock production, aquaculture production is derived from numerous, exceptionally diverse species that are typically in the early stages of domestication. Genetic improvement of production traits via well-designed, managed breeding programmes has great potential to help meet the rising seafood demand driven by human population growth. Supported by continuous advances in sequencing and bioinformatics, genomics is increasingly being applied across the broad range of aquaculture species and at all stages of the domestication process to optimize selective breeding. In the future, combining genomic selection with biotechnological innovations, such as genome editing and surrogate broodstock technologies, may further expedite genetic improvement in aquaculture.Genetic improvement of production traits in aquaculture has great potential to help meet the rising seafood demands driven by human population growth. The authors review how genomics is being applied to aquaculture species at all stages of the domestication process to optimize selective breeding.

Amoebic gill disease (AGD) is one of the largest threats to salmon aquaculture, causing serious economic and animal welfare burden. Treatments can be expensive and environmentally damaging, hence the need for alternative strategies. Breeding for disease resistance can contribute to prevention and control of AGD, providing long-term cumulative benefits in selected stocks. The use of genomic selection can expedite selection for disease resistance due to improved accuracy compared to pedigree-based approaches. The aim of this work was to quantify and characterize genetic variation in AGD resistance in salmon, the genetic architecture of the trait, and the potential of genomic selection to contribute to disease control. An AGD challenge was performed in ∼1,500 Atlantic salmon, using gill damage and amoebic load as indicator traits for host resistance. Both traits are heritable (h2 ∼0.25-0.30) and show high positive correlation, indicating they may be good measurements of host resistance to AGD. While the genetic architecture of resistance appeared to be largely polygenic in nature, two regions on chromosome 18 showed suggestive association with both AGD resistance traits. Using a cross-validation approach, genomic prediction accuracy was up to 18% higher than that obtained using pedigree, and a reduction in marker density to ∼2,000 SNPs was sufficient to obtain accuracies similar to those obtained using the whole dataset. This study indicates that resistance to AGD is a suitable trait for genomic selection, and the addition of this trait to Atlantic salmon breeding programs can lead to more resistant stocks.

Background Flavobacterium columnare is the pathogen agent of columnaris disease, a major emerging disease that affects rainbow trout aquaculture. Selective breeding using genomic selection has potential to achieve cumulative improvement of the host resistance. However, genomic selection is expensive partly because of the cost of genotyping large numbers of animals using high-density single nucleotide polymorphism (SNP) arrays. The objective of this study was to assess the efficiency of genomic selection for resistance to F. columnare using in silico low-density (LD) panels combined with imputation. After a natural outbreak of columnaris disease, 2874 challenged fish and 469 fish from the parental generation (n = 81 parents) were genotyped with 27,907 SNPs. The efficiency of genomic prediction using LD panels was assessed for 10 panels of different densities, which were created in silico using two sampling methods, random and equally spaced. All LD panels were also imputed to the full 28K HD panel using the parental generation as the reference population, and genomic predictions were re-evaluated. The potential of prioritizing SNPs that are associated with resistance to F. columnare was also tested for the six lower-density panels . Results The accuracies of both imputation and genomic predictions were similar with random and equally-spaced sampling of SNPs. Using LD panels of at least 3000 SNPs or lower-density panels (as low as 300 SNPs) combined with imputation resulted in accuracies that were comparable to those of the 28K HD panel and were 11% higher than the pedigree-based predictions. Conclusions Compared to using the commercial HD panel, LD panels combined with imputation may provide a more affordable approach to genomic prediction of breeding values, which supports a more widespread adoption of genomic selection in aquaculture breeding programmes.

Genomic selection enables cumulative genetic gains in key production traits such as disease resistance, playing an important role in the economic and environmental sustainability of aquaculture production. However, it requires genome-wide genetic marker data on large populations, which can be prohibitively expensive. Genotype imputation is a cost-effective method for obtaining high-density genotypes, but its value in aquaculture breeding programs which are characterized by large full-sibling families has yet to be fully assessed. The aim of this study was to optimize the use of low-density genotypes and evaluate genotype imputation strategies for cost-effective genomic prediction. Phenotypes and genotypes (78,362 SNPs) were obtained for 610 individuals from a Scottish Atlantic salmon breeding program population (Landcatch, UK) challenged with sea lice, Lepeophtheirus salmonis. The genomic prediction accuracy of genomic selection was calculated using GBLUP approaches and compared across SNP panels of varying densities and composition, with and without imputation. Imputation was tested when parents were genotyped for the optimal SNP panel, and offspring were genotyped for a range of lower density imputation panels. Reducing SNP density had little impact on prediction accuracy until 5,000 SNPs, below which the accuracy dropped. Imputation accuracy increased with increasing imputation panel density. Genomic prediction accuracy when offspring were genotyped for just 200 SNPs, and parents for 5,000 SNPs, was 0.53. This accuracy was similar to the full high density and optimal density dataset, and markedly higher than using 200 SNPs without imputation. These results suggest that imputation from very low to medium density can be a cost-effective tool for genomic selection in Atlantic salmon breeding programs.

In European seabass ( Dicentrarchus labrax ), dietary tryptophan (TRP) surplus has a notable modulatory effect on the hypothalamic–pituitary–interrenal axis under chronic stress and acute inflammation, affecting cortisol levels and neuroendocrine- and immune-related gene expression. A transcriptomic approach (RNA-seq) was applied to head-kidney samples of fish submitted to confinement stress and/or acute inflammation to uncover the biological mechanisms behind these effects. Undisturbed seabass fed dietary TRP supplementation showed an up-regulation of various innate immune functions, contrasting previous studies which indicated mainly a TRP regulatory role. Upon bacterial injection, TRP-fed fish showed a transcriptomic profile similar to their counterparts fed on control diet, indicating TRP’s inability to modulate immune mechanisms under bacterial challenge. Under confinement stress, TRP-fed fish exhibited a molecular profile similar to unstressed control fish, highlighting TRP’s role in mitigating stress. However, combining dietary TRP supplementation with confinement stress and immune stimulation by bacterial inoculation resulted in a unique molecular profile. Stressed fish fed TRP did not show the restorative effect of immune stimulation on carbohydrate metabolism and showed downregulated genes related to glycolysis and glycogenolysis. Additionally, transcription upregulation in these fish after bacterial injection included terms related to serine and steroid metabolism (carboxyl ester lipase 2), indicating tryptophan-induced changes in lipid mobilization in the head-kidney, potentially affecting cortisol synthesis and other hormones.

Structural variants (SVs) are a major source of genetic and phenotypic variation, but remain challenging to accurately type and are hence poorly characterized in most species. We present an approach for reliable SV discovery in non-model species using whole genome sequencing and report 15,483 high-confidence SVs in 492 Atlantic salmon ( Salmo salar L.) sampled from a broad phylogeographic distribution. These SVs recover population genetic structure with high resolution, include an active DNA transposon, widely affect functional features, and overlap more duplicated genes retained from an ancestral salmonid autotetraploidization event than expected. Changes in SV allele frequency between wild and farmed fish indicate polygenic selection on behavioural traits during domestication, targeting brain-expressed synaptic networks linked to neurological disorders in humans. This study offers novel insights into the role of SVs in genome evolution and the genetic architecture of domestication traits, along with resources supporting reliable SV discovery in non-model species. This study presents and validates a novel approach to reliably identify structural variations (SVs) in non-model genomes using whole genome sequencing, which was used to detect 15,483 SVs in 492 Atlantic salmon, shedding light on their roles in genome evolution and the genetic architecture of domestication.

Background Gene expression analysis by reverse transcription quantitative PCR (qPCR) is the most widely used method for analyzing the expression of a moderate number of genes and also for the validation of microarray results. Several issues are crucial for a successful qPCR study, particularly the selection of internal reference genes for normalization and efficiency determination. There is no agreement on which method is the best to detect the most stable genes neither on how to perform efficiency determination. In this study we offer a comprehensive evaluation of the characteristics of reference gene selection methods and how to decide which one is more reliable when they show discordant outcomes. Also, we analyze the current efficiency calculation controversy. Our dataset is composed by gonad samples of turbot at different development times reared at different temperatures. Turbot ( Scophthalmus maximus ) is a relevant marine aquaculture European species with increasing production in the incoming years. Since females largely outgrow males, identification of genes related to sex determination, gonad development and reproductive behavior, and analysis of their expression profiles are of primary importance for turbot industry. Results We analyzed gene stability of six reference genes: RPS4 , RPL17 , GAPDH , ACTB , UBQ and B2M using the comparative delta-CT method, Bestkeeper, NormFinder and GeNorm approaches in gonad samples of turbot. Supported by descriptive statistics, we found NormFinder to be the best method, while on the other side, GeNorm results proved to be unreliable. According to our analysis, UBQ and RPS4 were the most stable genes, while B2M was the least stable gene. We also analyzed the efficiency calculation softwares LinRegPCR, LREanalyzer, DART and PCR-Miner and we recommend LinRegPCR for research purposes since it does not systematically overestimate efficiency. Conclusion Our results indicate that NormFinder and LinRegPCR are the best approaches for reference gene selection and efficiency determination, respectively. We also recommend the use of UBQ and RPS4 for normalization of gonad development samples in turbot.

Background Gill health is one of the main concerns for Atlantic salmon aquaculture, and Amoebic Gill Disease (AGD), attributable to infection by the amoeba Neoparamoeba perurans, is a frequent cause of morbidity. In the absence of preventive measures, increasing genetic resistance of salmon to AGD via selective breeding can reduce the incidence of the disease and mitigate gill damage. Understanding the mechanisms leading to AGD resistance and the underlying causative genomic features can aid in this effort, while also providing critical information for the development of other control strategies. AGD resistance is considered to be moderately heritable, and several putative QTL have been identified. The aim of the current study was to improve understanding of the mechanisms underlying AGD resistance, and to identify putative causative genomic factors underlying the QTL. To achieve this, RNA was extracted from the gill and head kidney of AGD resistant and susceptible animals following a challenge with N. perurans , and sequenced. Results Comparison between resistant and susceptible animals primarily highlighted differences mainly in the local immune response in the gill, involving red blood cell genes and genes related to immune function and cell adhesion. Differentially expressed immune genes pointed to a contrast in Th2 and Th17 responses, which is consistent with the increased heritability observed after successive challenges with the amoeba. Five QTL-region candidate genes showed differential expression, including a gene connected to interferon responses ( GVINP1 ), a gene involved in systemic inflammation ( MAP4K4 ), and a positive regulator of apoptosis ( TRIM39 ). Analyses of allele-specific expression highlighted a gene in the QTL region on chromosome 17, cellular repressor of E1A-stimulated genes 1 ( CREG1 ), showing allelic differential expression suggestive of a cis-acting regulatory variant. Conclusions In summary, this study provides new insights into the mechanisms of resistance to AGD in Atlantic salmon, and highlights candidate genes for further functional studies that can further elucidate the genomic mechanisms leading to resistance and contribute to enhancing salmon health via improved genomic selection.

Interactions between host genetics and the resident microbiota are complex. Understanding these interactions offers interesting alternatives for addressing gill health and disease resistance in salmonids. Amoebic gill disease (AGD), caused by Neoparamoeba perurans , remains a threat to Atlantic salmon, particularly in aquaculture where prevention and treatment options are scant. Selective breeding or genetic engineering towards AGD resilience presents viable prevention strategies. While several studies have addressed AGD resistance in Atlantic salmon using transcriptomic and quantitative genetic approaches, the influence of the gill microbiota as a genotypic encoded phenotype for AGD resilience remains underexplored. Addressing this, we leveraged a holo‐omic approach using 16S rRNA profiling and quantitative genetics, treating the microbiota as an extended resistance trait. In this small‐scale exploratory work, we investigated the microbiota of AGD‐challenged Atlantic salmon in terms of two common resistance indicator traits: gill score and amoebic load. We then performed a GWAS using the traditional indicator traits and traits of the microbiota. We found that the gill microbiota of the AGD‐affected salmon was dominated by two bacterial families, Simkaniaceae and Arcobacteraceae . Additionally microbial diversity and the relative abundance of Simkaniaceae , potentially derived from the amoeba, showed moderate variation with indicator traits. We identified several genomic regions that showed suggestive association with gill score and traits of the microbiota, and explored genes in these regions in relation to AGD resistance. Although the underlying mechanisms shaping gill microbiota dynamics in gill disease remain unknown, this study highlights the potential of addressing AGD through an integrative approach that considers the interplay between host genetics, the microbiota, and their roles in disease resistance.

Background Infectious Salmon Anaemia virus (ISAV) is an orthomyxovirus responsible for large losses in Atlantic salmon ( Salmo salar ) aquaculture. Current available treatments and vaccines are not fully effective, and therefore selective breeding to produce ISAV-resistant strains of Atlantic salmon is a high priority for the industry. Genomic selection and potentially genome editing can be applied to enhance the disease resistance of aquaculture stocks, and both approaches can benefit from increased knowledge on the genomic mechanisms of resistance to ISAV. To improve our understanding of the mechanisms underlying resistance to ISAV in Atlantic salmon we performed a transcriptomic study in ISAV-infected salmon with contrasting levels of resistance to this virus. Results Three different tissues (gills, head kidney and spleen) were collected on 12 resistant and 12 susceptible fish at three timepoints (pre-challenge, 7 and 14 days post challenge) and RNA sequenced. The transcriptomes of infected and non-infected fish and of resistant and susceptible fish were compared at each timepoint. The results show that the responses to ISAV are organ-specific; an important response to the infection was observed in the head kidney, with up-regulation of immune processes such as interferon and NLR pathways, while in gills and spleen the response was more moderate. In addition to immune related genes, our results suggest that other processes such as ubiquitination and ribosomal processing are important during early infection with ISAV. Moreover, the comparison between resistant and susceptible fish has also highlighted some interesting genes related to ubiquitination, intracellular transport and the inflammasome. Conclusions Atlantic salmon infection by ISAV revealed an organ-specific response, implying differential function during the infection. An immune response was observed in the head kidney in these early timepoints, while gills and spleen showed modest responses in comparison. Comparison between resistance and susceptible samples have highlighted genes of interest for further studies, for instance those related to ubiquitination or the inflammasome.