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

BACKGROUND: Pisciricketssia 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. METHODS: 2,601 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. RESULTS: Genome 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. CONCLUSIONS: Due 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.

Genome-scale comparative analysis for host resistance against sea lice between Atlantic salmon and rainbow trout.

Sea lice (Caligus rogercresseyi) is an ectoparasite which causes major production losses in the salmon aquaculture industry worldwide. Atlantic salmon (Salmo salar) and rainbow trout (Oncorhynchus mykiss) are two of the most susceptible salmonid species to sea lice infestation. The objectives of this study were to: (1) identify genomic regions associated with resistance to Caligus rogercresseyi in Atlantic salmon and rainbow trout by performing single-step Genome-Wide Association studies (ssGWAS), and (2) identify candidate genes related to trait variation based on exploring orthologous genes within the associated regions across species. A total of 2626 Atlantic salmon and 2643 rainbow trout were challenged and genotyped with 50 K and 57 K SNP panels, respectively. We ran two independent ssGWAS for sea lice resistance on each species and identified 7 and 13 regions explaining more than 1% of the genetic variance for the trait, with the most important regions explaining 3% and 2.7% for Atlantic salmon and rainbow trout, respectively. We identified genes associated with immune response, cytoskeleton function, and cell migration when focusing on important genomic regions for each species. Moreover, we found 15 common orthogroups which were present in more than one associated genomic region, within- or between-species; however, only one orthogroup showed a clear potential biological relevance in the response against sea lice. For instance, dual-specificity protein phosphatase 10-like (dusp10) and dual-specificity protein phosphatase 8 (dusp8) were found in genomic regions associated with lice density in Atlantic salmon and rainbow trout, respectively. Dusp10 and dusp8 are modulators of the MAPK pathway and might be involved in the differences of the inflammation response between lice resistant and susceptible fish from both species. Our results provide further knowledge on candidate genes related to sea lice resistance and may help establish better control for sea lice in fish populations.

Single-Step Genome-Wide Association Study for Resistance to Piscirickettsia salmonis in Rainbow Trout (Oncorhynchus mykiss).

One of the main pathogens affecting rainbow trout (Oncorhynchus mykiss) farming is the facultative intracellular bacteria Piscirickettsia salmonis Current treatments, such as antibiotics and vaccines, have not had the expected effectiveness in field conditions. Genetic improvement by means of selection for resistance is proposed as a viable alternative for control. Genomic information can be used to identify the genomic regions associated with resistance and enhance the genetic evaluation methods to speed up the genetic improvement for the trait. The objectives of this study were to i) identify the genomic regions associated with resistance to P. salmonis; and ii) identify candidate genes associated with the trait in rainbow trout. We experimentally challenged 2,130 rainbow trout with P. salmonis and genotyped them with a 57 K single nucleotide polymorphism (SNP) array. Resistance to P. salmonis was defined as time to death (TD) and as binary survival (BS). Significant heritabilities were estimated for TD and BS (0.48 ± 0.04 and 0.34 ± 0.04, respectively). A total of 2,047 fish and 26,068 SNPs passed quality control for samples and genotypes. Using a single-step genome wide association analysis (ssGWAS) we identified four genomic regions explaining over 1% of the genetic variance for TD and three for BS. Interestingly, the same genomic region located on Omy27 was found to explain the highest proportion of genetic variance for both traits (2.4 and 1.5% for TD and BS, respectively). The identified SNP in this region is located within an exon of a gene related with actin cytoskeletal organization, a protein exploited by P. salmonis during infection. Other important candidate genes identified are related with innate immune response and oxidative stress. The moderate heritability values estimated in the present study show it is possible to improve resistance to P. salmonis through artificial selection in the rainbow trout population studied here. Furthermore, our results suggest a polygenic genetic architecture for the trait and provide novel insights into the candidate genes underpinning resistance to P. salmonis in O. mykiss.

Comparative Genomic Analysis of Three Salmonid Species Identifies Functional Candidate Genes Involved in Resistance to the Intracellular Bacterium Piscirickettsia salmonis.

Piscirickettsia salmonis is the etiologic agent of salmon rickettsial syndrome (SRS) and is responsible for considerable economic losses in salmon aquaculture. The bacterium affects coho salmon (CS; Oncorhynchus kisutch), Atlantic salmon (AS; Salmo salar), and rainbow trout (RT; Oncorhynchus mykiss) in several countries, including Norway, Canada, Scotland, Ireland, and Chile. We used Bayesian genome-wide association study analyses to investigate the genetic architecture of resistance to P. salmonis in farmed populations of these species. Resistance to SRS was defined as the number of days to death and as binary survival (BS). A total of 828 CS, 2130 RT, and 2601 AS individuals were phenotyped and then genotyped using double-digest restriction site-associated DNA sequencing and 57K and 50K Affymetrix® Axiom® single nucleotide polymorphism (SNP) panels, respectively. Both traits of SRS resistance in CS and RT appeared to be under oligogenic control. In AS, there was evidence of polygenic control of SRS resistance. To identify candidate genes associated with resistance, we applied a comparative genomics approach in which we systematically explored the complete set of genes adjacent to SNPs, which explained more than 1% of the genetic variance of resistance in each salmonid species (533 genes in total). Thus, genes were classified based on the following criteria: i) shared function of their protein domains among species, ii) shared orthology among species, iii) proximity to the SNP explaining the highest proportion of the genetic variance, and iv) presence in more than one genomic region explaining more than 1% of the genetic variance within species. Our results allowed us to identify 120 candidate genes belonging to at least one of the four criteria described above. Of these, 21 of them were part of at least two of the criteria defined above and are suggested to be strong functional candidates influencing P. salmonis resistance. These genes are related to diverse biological processes, such as kinase activity, GTP hydrolysis, helicase activity, lipid metabolism, cytoskeletal dynamics, inflammation, and innate immune response, which seem essential in the host response against P. salmonis infection. These results provide fundamental knowledge on the potential functional genes underpinning resistance against P. salmonis in three salmonid species.

Loci de caracteres quantitativos (qtl) em peixes / Quantitative trait loci (qtl) in fishes / Loci de caracteres cuantitativos (qtl) en peces

Entre as aplicações do mapeamento genômico está a procura por loci de caracteres quantitativos, influenciando características economicamente importantes na produção animal. A metodologia identifica relações entre variações no nível do DNA e valores fenotípicos. Esses dados fenotípicos podem ser referentes à características de herança simples ou quantitativa (herança poligênica). Em anos recentes, análises têm sido focadas, principalmente em caracteres quantitativos, pois são a base das características de produção. No entanto, a natureza poligênica desses caracteres com variação contínua dificulta análises clássicas, por meio de cruzamento para isolamento gênico, principalmente em razão da falta de segregação fenotípica discreta. Nesses casos, regiões do DNA responsáveis pelo fenótipo são definidas como QTL (Quantitative Trait Loci). Sua identificação pode ser realizada por varredura genômica ou análise de cromossomos individualmente. Um próximo passo é identificar os genes presentes nas regiões próximas a marcadores ligados ao QTL. O procedimento é realizado por meio de mapeamento fino, com o emprego de um maior número de marcadores próximos a região de localização do QTL. Este refinamento da análise de ligação, ou saturação da região de mapeamento, permite reduzir o tamanho da região mapeada, e, portanto, reduzir o número de possíveis genes relacionados ao QTL...

Among the applications of genome mapping is the search for loci that influence economically important quantitative traits in animal production. The methodology identifies the relationship among variations at DNA level and phenotypic values. These phenotypic data may be referent to traits of simple or quantitative (polygenic) inheritance. In recent years, analyses have been mainly focused in quantitative traits, since these are usually production traits. However, the polygenic nature of these particular characters with continuous variation makes it difficult to employ classical analyses of crosses for gene isolation, mainly due to the lack of discrete phenotypic segregation. In these cases, DNA regions responsible for the phenotype are defined as QTL (Quantitative Trait Loci). Its identification can be done by a whole-genome screening or analyzing chromosomes individually. A next step is to identify the genes present in the regions next to markers linked to QTL. The procedure is done by fine mapping, using a larger number of markers next to the region of the QTL position. This refinement of the linkage analysis or saturation of the mapping region allows reducing the size of the mapped region and thus reduce the number of possible genes related to the QTL...

Entre las aplicaciones del mapeo genómico está la búsqueda por loci de caracteres cuantitativos, influenciando características económicamente relevantes en la producción animal. La metodología identifica relaciones entre variaciones a nivel del ADN y valores fenotípicos. Esos datos fenotípicos pueden ser referentes a las características de herencia simple o cuantitativa (herencia poligénica). En años recientes, análisis han sido enfocadas, principalmente en caracteres cuantitativos, pues son la base de las características de producción. Sin embargo, la naturaleza poligénica de esos caracteres con variación continua dificulta análisis clásicos, que utiliza cruzamientos para aislamiento génico, principalmente en razón de la falta de segregación fenotípica discreta. En esos casos, regiones del ADN responsables por el fenotipo son definidas como QTL (Quantitative Trait Loci). Su identificación puede ser realizada por barredura genómica o por análisis individual de cromosomas. Un próximo paso es identificar los genes presentes en las regiones próximas a los marcadores unidos al QTL...