Jean Paul Lhorente

Genomewide single nucleotide polymorphism discovery in Atlantic salmon (Salmo salar ) : validation in wild and farmed American and European populations

A considerable number of single nucleotide polymorphisms (SNPs) are required to elucidate genotype–phenotype associations and determine the molecular basis of important traits. In this work, we carried out de novo SNP discovery accounting for both genome duplication and genetic variation from American and European salmon populations. A total of 9 736 473 nonredundant SNPs were identified across a set of 20 fish by whole‐genome sequencing. After applying six bioinformatic filtering steps, 200 K SNPs were selected to develop an Affymetrix Axiom® myDesign Custom Array. This array was used to genotype 480 fish representing wild and farmed salmon from Europe, North America and Chile. A total of 159 099 (79.6%) SNPs were validated as high quality based on clustering properties. A total of 151 509 validated SNPs showed a unique position in the genome. When comparing these SNPs against 238 572 markers currently available in two other Atlantic salmon arrays, only 4.6% of the SNP overlapped with the panel developed in this study. This novel high‐density SNP panel will be very useful for the dissection of economically and ecologically relevant traits, enhancing breeding programmes through genomic selection as well as supporting genetic studies in both wild and farmed populations of Atlantic salmon using high‐resolution genomewide information.

Genome-wide association analysis reveals loci associated with resistance against Piscirickettsia salmonis in two Atlantic salmon (Salmo salar L.) chromosomes

BackgroundPisciricketssia salmonis is the causal agent of Salmon Rickettsial Syndrome (SRS), which affects salmon species and causes severe economic losses. Selective breeding for disease resistance represents one approach for controlling SRS in farmed Atlantic salmon. Knowledge concerning the architecture of the resistance trait is needed before deciding on the most appropriate approach to enhance artificial selection for P. salmonis resistance in Atlantic salmon. The purpose of the study was to dissect the genetic variation in the resistance to this pathogen in Atlantic salmon.Methods2,601 Atlantic salmon smolts were experimentally challenged against P. salmonis by means of intra-peritoneal injection. These smolts were the progeny of 40 sires and 118 dams from a Chilean breeding population. Mortalities were recorded daily and the experiment ended at day 40 post-inoculation. Fish were genotyped using a 50K Affymetrix® Axiom® myDesignTM Single Nucleotide Polymorphism (SNP) Genotyping Array. A Genome Wide Association Analysis was performed on data from the challenged fish. Linear regression and logistic regression models were tested.ResultsGenome Wide Association Analysis indicated that resistance to P. salmonis is a moderately polygenic trait. There were five SNPs in chromosomes Ssa01 and Ssa17 significantly associated with the traits analysed. The proportion of the phenotypic variance explained by each marker is small, ranging from 0.007 to 0.045. Candidate genes including interleukin receptors and fucosyltransferase have been found to be physically linked with these genetic markers and may play an important role in the differential immune response against this pathogen.ConclusionsDue to the small amount of variance explained by each significant marker we conclude that genetic resistance to this pathogen can be more efficiently improved with the implementation of genetic evaluations incorporating genotype information from a dense SNP array.

Disease Resistance in Atlantic Salmon (Salmo salar): Coinfection of the Intracellular Bacterial Pathogen Piscirickettsia salmonis and the Sea Louse Caligus rogercresseyi

Background Naturally occurring coinfections of pathogens have been reported in salmonids, but their consequences on disease resistance are unclear. We hypothesized that 1) coinfection of Caligus rogercresseyi reduces the resistance of Atlantic salmon to Piscirickettsia salmonis; and 2) coinfection resistance is a heritable trait that does not correlate with resistance to a single infection. Methodology In total, 1,634 pedigreed Atlantic salmon were exposed to a single infection (SI) of P. salmonis (primary pathogen) or coinfection with C. rogercresseyi (secondary pathogen). Low and high level of coinfection were evaluated (LC = 44 copepodites per fish; HC = 88 copepodites per fish). Survival and quantitative genetic analyses were performed to determine the resistance to the single infection and coinfections. Main Findings C. rogercresseyi significantly increased the mortality in fish infected with P. salmonis (SI mortality = 251/545; LC mortality = 544/544 and HC mortality = 545/545). Heritability estimates for resistance to P. salmonis were similar and of medium magnitude in all treatments (h 2 SI = 0.23±0.07; h 2 LC = 0.17±0.08; h 2 HC = 0.24±0.07). A large and significant genetic correlation with regard to resistance was observed between coinfection treatments (rg LC-HC = 0.99±0.01) but not between the single and coinfection treatments (rg SI-LC = −0.14±0.33; rg SI-HC = 0.32±0.34). Conclusions/Significance C. rogercresseyi, as a secondary pathogen, reduces the resistance of Atlantic salmon to the pathogen P. salmonis. Resistance to coinfection of Piscirickettsia salmonis and Caligus rogercresseyi in Atlantic salmon is a heritable trait. The absence of a genetic correlation between resistance to a single infection and resistance to coinfection indicates that different genes control these processes. Coinfection of different pathogens and resistance to coinfection needs to be considered in future research on salmon farming, selective breeding and conservation.

The consequences of including non-additive effects on the genetic evaluation of harvest body weight in Coho salmon (Oncorhynchus kisutch)

BackgroundIn this study, we used different animal models to estimate genetic and environmental variance components on harvest weight in two populations of Oncorhynchus kisutch, forming two classes i.e. odd- and even-year spawners.MethodsThe models used were: additive, with and without inbreeding as a covariable (A + F and A respectively); additive plus common environmental due to full-sib families and inbreeding (A + C + F); additive plus parental dominance and inbreeding (A + D + F); and a full model (A + C + D + F). Genetic parameters and breeding values obtained by different models were compared to evaluate the consequences of including non-additive effects on genetic evaluation.ResultsIncluding inbreeding as a covariable did not affect the estimation of genetic parameters, but heritability was reduced when dominance or common environmental effects were included. A high heritability for harvest weight was estimated in both populations (even = 0.46 and odd = 0.50) when simple additive models (A + F and A) were used. Heritabilities decreased to 0.21 (even) and 0.37 (odd) when the full model was used (A + C + D + F). In this full model, the magnitude of the dominance variance was 0.19 (even) and 0.06 (odd), while the magnitude of the common environmental effect was lower than 0.01 in both populations. The correlation between breeding values estimated with different models was very high in all cases (i.e. higher than 0.98). However, ranking of the 30 best males and the 100 best females per generation changed when a high dominance variance was estimated, as was the case in one of the two populations (even).ConclusionsDominance and common environmental variance may be important components of variance in harvest weight in O. kisutch, thus not including them may produce an overestimation of the predicted response; furthermore, genetic evaluation was seen to be partially affected, since the ranking of selected animals changed with the inclusion of non-additive effects in the animal model.

Genomic Prediction Accuracy for Resistance Against Piscirickettsia salmonis in Farmed Rainbow Trout

Salmonid rickettsial syndrome (SRS), caused by the intracellular bacterium Piscirickettsia salmonis, is one of the main diseases affecting rainbow trout (Oncorhynchus mykiss) farming. To accelerate genetic progress, genomic selection methods can be used as an effective approach to control the disease. The aims of this study were: (i) to compare the accuracy of estimated breeding values using pedigree-based best linear unbiased prediction (PBLUP) with genomic BLUP (GBLUP), single-step GBLUP (ssGBLUP), Bayes C, and Bayesian Lasso (LASSO); and (ii) to test the accuracy of genomic prediction and PBLUP using different marker densities (0.5, 3, 10, 20, and 27 K) for resistance against P. salmonis in rainbow trout. Phenotypes were recorded as number of days to death (DD) and binary survival (BS) from 2416 fish challenged with P. salmonis. A total of 1934 fish were genotyped using a 57 K single-nucleotide polymorphism (SNP) array. All genomic prediction methods achieved higher accuracies than PBLUP. The relative increase in accuracy for different genomic models ranged from 28 to 41% for both DD and BS at 27 K SNP. Between different genomic models, the highest relative increase in accuracy was obtained with Bayes C (∼40%), where 3 K SNP was enough to achieve a similar accuracy to that of the 27 K SNP for both traits. For resistance against P. salmonis in rainbow trout, we showed that genomic predictions using GBLUP, ssGBLUP, Bayes C, and LASSO can increase accuracy compared with PBLUP. Moreover, it is possible to use relatively low-density SNP panels for genomic prediction without compromising accuracy predictions for resistance against P. salmonis in rainbow trout.

Genomic Predictions and Genome-Wide Association Study of Resistance Against Piscirickettsia salmonis in Coho Salmon (Oncorhynchus kisutch) Using ddRAD Sequencing

Piscirickettsia salmonis is one of the main infectious diseases affecting coho salmon (Oncorhynchus kisutch) farming, and current treatments have been ineffective for the control of this disease. Genetic improvement for P. salmonis resistance has been proposed as a feasible alternative for the control of this infectious disease in farmed fish. Genotyping by sequencing (GBS) strategies allow genotyping of hundreds of individuals with thousands of single nucleotide polymorphisms (SNPs), which can be used to perform genome wide association studies (GWAS) and predict genetic values using genome-wide information. We used double-digest restriction-site associated DNA (ddRAD) sequencing to dissect the genetic architecture of resistance against P. salmonis in a farmed coho salmon population and to identify molecular markers associated with the trait. We also evaluated genomic selection (GS) models in order to determine the potential to accelerate the genetic improvement of this trait by means of using genome-wide molecular information. A total of 764 individuals from 33 full-sib families (17 highly resistant and 16 highly susceptible) were experimentally challenged against P. salmonis and their genotypes were assayed using ddRAD sequencing. A total of 9,389 SNPs markers were identified in the population. These markers were used to test genomic selection models and compare different GWAS methodologies for resistance measured as day of death (DD) and binary survival (BIN). Genomic selection models showed higher accuracies than the traditional pedigree-based best linear unbiased prediction (PBLUP) method, for both DD and BIN. The models showed an improvement of up to 95% and 155% respectively over PBLUP. One SNP related with B-cell development was identified as a potential functional candidate associated with resistance to P. salmonis defined as DD.

Single-step genomic evaluation improves accuracy of breeding value predictions for resistance to infectious pancreatic necrosis virus in rainbow trout

The aim of this study was to compare the accuracy of breeding values (EBVs) predicted using the traditional pedigree based Best Linear Unbiased Prediction (PBLUP) and the single-step genomic Best Linear Unbiased Prediction (ssGBLUP) for resistance against infectious pancreatic necrosis virus (IPNV) in rainbow trout. A total of 2278 animals were challenged against IPNV and 768 individuals were genotyped using a 57 K single nucleotide polymorphism array for rainbow trout. Accuracies for both methods were assessed using five-fold cross-validation. The heritabilities were higher for PBLUP compared to ssGBLUP. The ssGBLUP accuracies outperformed PBLUP in 7 and 11% for days to death and binary survival, respectively. The ssGBLUP could be an alternative approach to improve the accuracy of breeding values for resistance against infectious pancreatic necrosis virus in rainbow trout, using information from genotyped and non-genotyped animals.

Comparing genomic signatures of domestication in two Atlantic salmon (Salmo salar L) populations with different geographical origins

Selective breeding and genetic improvement have left detectable signatures on the genomes of domestic species. The elucidation of such signatures is fundamental for detecting genomic regions of biological relevance to domestication and improving management practices. In aquaculture, domestication was carried out independently in different locations worldwide, which provides opportunities to study the parallel effects of domestication on the genome of individuals that have been selected for similar traits. In this study, we aimed to detect potential genomic signatures of domestication in two independent pairs of wild/domesticated Atlantic salmon populations of Canadian and Scottish origins, respectively. Putative genomic regions under divergent selection were investigated using a 200K SNP array by combining three different statistical methods based either on allele frequencies (LFMM, Bayescan) or haplotype differentiation (Rsb). We identified 337 and 270 SNPs potentially under divergent selection in wild and hatchery populations of Canadian and Scottish origins, respectively. We observed little overlap between results obtained from different statistical methods, highlighting the need to test complementary approaches for detecting a broad range of genomic footprints of selection. The vast majority of the outliers detected were population‐specific but we found four candidate genes that were shared between the populations. We propose that these candidate genes may play a role in the parallel process of domestication. Overall, our results suggest that genetic drift may have override the effect of artificial selection and/or point toward a different genetic basis underlying the expression of similar traits in different domesticated strains. Finally, it is likely that domestication may predominantly target polygenic traits (e.g., growth) such that its genomic impact might be more difficult to detect with methods assuming selective sweeps.

Whole genome linkage disequilibrium and effective population size in a coho salmon (Oncorhynchus kisutch) breeding population

The estimation of linkage disequilibrium between molecular markers within a population is critical when establishing the minimum number of markers required for association studies, genomic selection and for inferring historical events influencing different populations. This work aimed to evaluate the extent and decay of linkage disequilibrium in a coho salmon breeding population using ddRAD genomic markers. Linkage disequilibrium was estimated between a total of 7,505 SNPs found in 62 individuals (33 dams and 29 sires) from the breeding population. The makers encompass all 30 coho salmon chromosomes and comprise 1,655.19 Mb of the genome. The average density of markers per chromosome ranged from 3.45 to 6.11 per 1 Mbp. The minor allele frequency averaged 0.20 (with a range from 0.08 to 0.50). The overall average linkage disequilibrium among SNPs pairs measured as r2 was 0.054. The Average r2 value decreased with increasing physical distance, with values ranging from 0.37 to 0.054 at distances lower than 1 kb and up to 10 Mb, respectively. An r2 threshold of 0.1 was reached at distance of approximately 1.3 Mb. Chromosomes Okis05, Okis15 and Okis28 showed high levels of linkage disequilibrium (> 0.20 at distances lower than 1 Mb). Average r2 values were lower than 0.1 for all chromosomes at distances greater than 4 Mb. Linkage disequilibrium values suggest that whole genome association and selection studies could be performed using about 75,000 SNPs in aquaculture populations (depending on the trait under investigation). From the identified SNPs, an effective population size of 100 was estimated for the population 10 generation ago, and 1,000, for 139 generations ago. Based on the extent of r2 decay, we suggest that at least 75,000 SNPs would be necessary for an association mapping study. Over 100,000 SNPs would be necessary for a high power study, in the current coho salmon population.

Discovery and functional annotation of quantitative trait loci affecting resistance to sea lice in Atlantic salmon

Sea lice (Caligus rogercresseyi) are ectoparasitic copepods which have a large negative economic and welfare impact in Atlantic salmon (Salmo salar) aquaculture, particularly in Chile. A multi-faceted prevention and control strategy is required to tackle lice, and selective breeding contributes via cumulative improvement of host resistance to the parasite. While host resistance has been shown to be heritable, little is yet known about the individual loci that contribute to this resistance, the potential underlying genes, and their mechanisms of action. In this study we took a multifaceted approach to identify and characterise quantitative trait loci (QTL) affecting hose resistance in a population of 2,688 Caligus-challenged Atlantic salmon post-smolts from a commercial breeding programme. We used low and medium density genotyping to collect genome-wide SNP marker data for all animals. Moderate heritablility estimates of 0.28 and 0.24 were obtained for lice density (as a measure of host resistance) and growth during infestation respectively. Three QTL explaining between 7 and 13 % of the genetic variation in resistance to sea lice (as represented by the traits of lice density) were detected on chromosomes 3, 18 and 21. Characterisation of these QTL regions was undertaken using RNA sequencing and pooled whole genome sequencing data. This resulted in the identification of a shortlist of potential underlying causative genes, and candidate functional mutations for further study. For example, candidates within the chromosome 3 QTL include a putative premature stop mutation in TOB1 (an anti-proliferative transcription factor involved in T cell regulation) and an uncharacterized protein which showed significant differential allelic expression (implying the existence of a cis-acting regulatory mutation). While host resistance to sea lice is polygenic in nature, the results of this study highlight significant QTL regions together explaining a moderate proportion of the heritability of the trait. Future investigation of these QTL may enable improved knowledge of the functional mechanisms of host resistance to sea lice, and incorporation of functional variants to improve genomic selection accuracy.