Genome-Wide Association and Genomic Selection for Resistance to Amoebic Gill Disease in Atlantic Salmon

Abstract 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.</jats:p

Optimizing Low-Cost Genotyping and Imputation Strategies for Genomic Selection in Atlantic Salmon

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 characterised by large full-sibling families has yet to be fully assessed. The aim of this study was to optimise 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

High resolution mapping of the recombination landscape of the phytopathogen Fusarium graminearum suggests two-speed genome evolution

International audienceRecombination is a major evolutionary force, increasing genetic diversity and permitting efficient coevolution of fungal pathogen(s) with their host(s). The ascomycete Fusarium graminearum is a devastating pathogen of cereal crops, and can contaminate food and feed with harmful mycotoxins. Previous studies have suggested a high adaptive potential of this pathogen, illustrated by an increase in pathogenicity and resistance to fungicides. In this study, we provide the first detailed picture of the crossover events occurring during meiosis and discuss the role of recombination in pathogen evolution. An experimental recombinant population (n = 88) was created and genotyped using 1306 polymorphic markers obtained from restriction site-associated DNA sequencing (RAD-seq) and aligned to the reference genome. The construction of a high-density linkage map, anchoring 99% of the total length of the reference genome, allowed the identification of 1451 putative crossovers, positioned at a median resolution of 24 kb. The majority of crossovers (87.2%) occurred in a relatively small portion of the genome (30%). All chromosomes demonstrated recombination-active sections, which had a near 15-fold higher crossover rate than non-active recombinant sections. The recombination rate showed a strong positive correlation with nucleotide diversity, and recombination-active regions were enriched for genes with a putative role in host-pathogen interaction, as well as putative diversifying genes. Our results confirm the preliminary analysis observed in other F. graminearum strains and suggest a conserved 'two-speed' recombination landscape. The consequences with regard to the evolutionary potential of this major fungal pathogen are also discussed

Gene Expression Response to Sea Lice in Atlantic Salmon Skin: RNA Sequencing Comparison Between Resistant and Susceptible Animals

Sea lice are parasitic copepods that cause large economic losses to salmon aquaculture worldwide. Frequent chemotherapeutic treatments are typically required to control this parasite, and alternative measures such as breeding for improved host resistance are desirable. Insight into the host–parasite interaction and mechanisms of host resistance can lead to improvements in selective breeding, and potentially novel treatment targets. In this study, RNA sequencing was used to study the skin transcriptome of Atlantic salmon (Salmo salar) parasitized with sea lice (Caligus rogercresseyi). The overall aims were to compare the transcriptomic profile of skin at louse attachment sites and “healthy” skin, and to assess differences in gene expression response between animals with varying levels of resistance to the parasite. Atlantic salmon pre-smolts were challenged with C. rogercresseyi, growth and lice count measurements were taken for each fish. 21 animals were selected and RNA-Seq was performed on skin from a louse attachment site, and skin distal to attachment sites for each animal. These animals were classified into family-balanced groups according to the traits of resistance (high vs. low lice count), and growth during infestation. Overall comparison of skin from louse attachment sites vs. healthy skin showed that 4,355 genes were differentially expressed, indicating local up-regulation of several immune pathways and activation of tissue repair mechanisms. Comparison between resistant and susceptible animals highlighted expression differences in several immune response and pattern recognition genes, and also myogenic and iron availability factors. Components of the pathways involved in differential response to sea lice may be targets for studies aimed at improved or novel treatment strategies, or to prioritize candidate functional polymorphisms to enhance genomic selection for host resistance in commercial salmon breeding programs

Potential of low-density genotype imputation for cost-efficient genomic selection for resistance to Flavobacterium columnare in rainbow trout (Oncorhynchus mykiss)

Background Flavobacterium columnare is the pathogen agent of columnaris disease, a major emerging disease that afects 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 efciency 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 fsh and 469 fsh from the parental generation (n=81 parents) were genotyped with 27,907 SNPs. The efciency of genomic prediction using LD panels was assessed for 10 panels of diferent 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 afordable approach to genomic prediction of breeding values, which supports a more widespread adoption of genomic selection in aquaculture breeding programme

Potential of genotyping-by-sequencing for genomic selection in livestock populations

International audienceBackground Next-generation sequencing techniques, such as genotyping-by-sequencing (GBS), provide alternatives to single nucleotide polymorphism (SNP) arrays. The aim of this work was to evaluate the potential of GBS compared to SNP array genotyping for genomic selection in livestock populations.MethodsThe value of GBS was quantified by simulation analyses in which three parameters were varied: (i) genome-wide sequence read depth (x) per individual from 0.01x to 20x or using SNP array genotyping; (ii) number of genotyped markers from 3000 to 300 000; and (iii) size of training and prediction sets from 500 to 50 000 individuals. The latter was achieved by distributing the total available x of 1000x, 5000x, or 10 000x per genotyped locus among the varying number of individuals. With SNP arrays, genotypes were called from sequence data directly. With GBS, genotypes were called from sequence reads that varied between loci and individuals according to a Poisson distribution with mean equal to x. Simulated data were analyzed with ridge regression and the accuracy and bias of genomic predictions and response to selection were quantified under the different scenarios.ResultsAccuracies of genomic predictions using GBS data or SNP array data were comparable when large numbers of markers were used and x per individual was ~1x or higher. The bias of genomic predictions was very high at a very low x. When the total available x was distributed among the training individuals, the accuracy of prediction was maximized when a large number of individuals was used that had GBS data with low x for a large number of markers. Similarly, response to selection was maximized under the same conditions due to increasing both accuracy and selection intensity.ConclusionsGBS offers great potential for developing genomic selection in livestock populations because it makes it possible to cover large fractions of the genome and to vary the sequence read depth per individual. Thus, the accuracy of predictions is improved by increasing the size of training populations and the intensity of selection is increased by genotyping a larger number of selection candidates

Assessment of Marine Gill Disease in Farmed Atlantic Salmon (Salmo salar) in Chile Using a Novel Total Gross Gill Scoring System:A Case Study

Gill disorders have become more prevalent and widespread in finfish aquaculture in recent years. Their aetiology is often considered to be multifactorial. Effective diagnosis, control and prevention are hindered by the lack of standardised methodologies to characterise the aetiological agents, which produce an array of clinical and pathological presentations. The aim of this study was to define a novel gross pathological scoring system suitable for field-based macroscopic assessment of complex or multifactorial gill disease in farmed Atlantic salmon, using samples derived from a gill disease outbreak in Chile. Clinical assessment of gross gill morphology was performed, and gill samples were collected for qPCR and histology. A novel total gill scoring system was developed, which assesses gross pathological changes combining both the presumptive or healed amoebic gill disease (AGD) and the presence of other types of gill lesions. This scoring system offers a standardised approach to characterise the severe proliferative pathologies in affected gills. This total gill scoring system can substantially contribute to the development of robust mitigation strategies and could be used as an indicator trait for incorporating resistance to multifactorial gill disease into breeding goals

A SNP in the 5' flanking region of the myostatin-1b gene is associated with harvest traits in Atlantic salmon (Salmo salar)

BACKGROUND: Myostatin (MSTN) belongs to the transforming growth factor-β superfamily and is a potent negative regulator of skeletal muscle development and growth in mammals. Most teleost fish possess two MSTN paralogues. However, as a consequence of a recent whole genome-duplication event, salmonids have four: MSTN-1 (−1a and -1b) and MSTN-2 (−2a and -2b). Evidence suggests that teleost MSTN plays a role in the regulation of muscle growth. In the current study, the MSTN-1b gene was re-sequenced and screened for SNP markers in a commercial population of Atlantic salmon. After genotyping 4,800 progeny for the discovered SNPs, we investigated their association with eight harvest traits - four body-weight traits, two ratios of weight traits, flesh colour and fat percentage - using a mixed model association analysis. RESULTS: Three novel SNPs were discovered in the MSTN-1b gene of Atlantic salmon. One of the SNPs, located within the 5′ flanking region (g.1086C > T), had a significant association with harvest traits (p < 0.05), specifically for: Harvest Weight (kg), Gutted Weight (kg), Deheaded Weight (kg) and Fillet Weight (kg). The haplotype-based association analysis was consistent with this result because the two haplotypes that showed a significant association with body-weight traits, hap4 and hap5 (p < 0.05 and p < 0.01, respectively), differ by a single substitution at the g.1086C > T locus. The alleles at g.1086C > T act in an additive manner and explain a small percentage of the genetic variation of these phenotypes. CONCLUSIONS: The association analysis revealed that g.1086C > T had a significant association with all body-weight traits under study. Although the SNP explains a small percentage of the variance, our results indicate that a variation in the 5′ flanking region of the myostatin gene is associated with the genetic regulation of growth in Atlantic salmon