Low-coverage whole-genome sequencing in livestock species for individual traceability and parentage testing

Altres ajuts: Acord transformatiu CRUE-CSICProcedures for genetic traceability of animal products and parentage testing mainly focus on microsatellites or SNPs panels. Nevertheless, current availability of high-throughput sequencing technologies must be considered as an appealing alternative. This research focused on the evaluation of low-coverage whole-genome sequencing for traceability and paternity testing purposes, within a context of evidential statistics. Analyses were performed on a simulation basis and assumed individuals with 30 100-Mb/100-cM chromosome pairs and ~1,000,000 polymorphic SNPs per chromosome. Ten independent populations were simulated under recombination and mutation with effective populations size 100 (generations 1-1000), 10,000 (generation 1001) and 25,000 (generation 1002), and this last generation was retained for analytical purposes. Appropriate both traceability and paternity tests were developed and evaluated on different high-throughput sequencing scenarios accounting for genome coverage depth (0.01×, 0.05×, 0.1× and 0.5×), length of base-pair reads (100, 1000 and 10,000 bp), and sequencing error rate (0%, 1% and 10%). Assuming true sequencing error rates and genotypic frequencies, 0.05× genome coverage depth guaranteed 100% sensitivity and specificity for traceability and paternity tests (n = 1000). Same results were obtained when sequencing error rate was arbitrarily set to 0, or the maximum value assumed during simulation (i.e., 1%). In a similar way, uncertainly about genotypic frecuencies did not impair sensitivity under 0.05× genome coverage, although it reduced specificity for paternity tests up to 85.2%. These results highlighted low-coverage whole-genome sequencing as a promising tool for the livestock and food industry with both technological and (maybe) economic advantages

Evidential segregation analysis for offspring sex ratio in rabbit and sheep populations

Altres ajuts: acords transformatius de la UABOffspring sex ratio has been found to be altered by environmental and genetic distortions in multiple species, against the Mendelian inheritance rules. However, little is known in livestock populations where it is essential to validate whether a polymorphic major gene with relevant effects may segregate in the target population. However, the current analytical tool (model FREQ) cannot handle new mutations in non-founder individuals, reducing the chance of detecting them. Our new analytical approach aimed to overcome this limitation in the context of evidential inference, a statistical framework based on the likelihood function as a robust objective measure of the strength of statistical evidence without variation from the sample size. Two field data sets from sheep and rabbit populations were used. Models evaluated environmental and inbreeding effects in both species. Our new approach assumed that the mutation primarily arose in an individual of the analyzed data set (model MUTj). Each sire was individually analyzed to determine the most plausible source for the new mutation, if any. The likelihood ratio (LR) against a reference parametrization without mutations (model NULL) was used to test the statistical relevance of systematic effects (LR ≥ 8) and models (LR ≥ 32). Both species revealed relevant departures for offspring sex ratio along the analyzed time frame with strong evidence for the year (LR = 1.4 × 10 in Ripollesa sheep and LR = 85.7 in MARET rabbits) and season (LR = 12.6 in MARET rabbits), although with a fluctuating pattern. The age of the dam reported weak evidence in both species (LR 32) was the Ripollesa sheep, with a ram three to six generations from the founders as the most likely source for a new mutation increasing the odds of daughters. The additive genetic effect of this model for the mutant allele also had strong evidence (LR = 1,195). Therefore, the MUT parametrization can be a valuable analytical tool to check for the possibility of new mutations along the pedigree files, not only before the founders

Parent-offspring genotyped trios unravelling genomic regions with gametic and genotypic epistatic transmission bias on the cattle genome

Several biological mechanisms affecting the sperm and ova fertility and viability at developmental stages of the reproductive cycle resulted in observable transmission ratio distortion (i.e., deviation from Mendelian expectations). Gene-by-gene interactions (or epistasis) could also potentially cause specific transmission ratio distortion patterns at different loci as unfavorable allelic combinations are under-represented, exhibiting deviation from Mendelian proportions. Here, we aimed to detect pairs of loci with epistatic transmission ratio distortion using 283,817 parent-offspring genotyped trios (sire-dam-offspring) of Holstein cattle. Allelic and genotypic parameterization for epistatic transmission ratio distortion were developed and implemented to scan the whole genome. Different epistatic transmission ratio distortion patterns were observed. Using genotypic models, 7, 19 and 6 pairs of genomic regions were found with decisive evidence with additive-by-additive, additive-by-dominance/dominance-by-additive and dominance-by-dominance effects, respectively. Using the allelic transmission ratio distortion model, more insight was gained in understanding the penetrance of single-locus distortions, revealing 17 pairs of SNPs. Scanning for the depletion of individuals carrying pairs of homozygous genotypes for unlinked loci, revealed 56 pairs of SNPs with recessive epistatic transmission ratio distortion patterns. The maximum number of expected homozygous offspring, with none of them observed, was 23. Finally, in this study, we identified candidate genomic regions harboring epistatic interactions with potential biological implications in economically important traits, such as reproduction

Genomic screening of allelic and genotypic transmission ratio distortion in horse

The phenomenon in which the expected Mendelian inheritance is altered is known as transmission ratio distortion (TRD). The TRD analysis relies on the study of the transmission of one of the two alleles from a heterozygous parent to the offspring. These distortions are due to biological mechanisms affecting gametogenesis, embryo development and/or postnatal viability, among others. In this study, TRD phenomenon was characterized in horses using SNP-by-SNP model by TRDscan v.2.0 software. A total of 1,041 Pura Raza Español breed horses were genotyped with 554,634 SNPs. Among them, 277 horses genotyped in trios (stallion-mare-offspring) were used to perform the TRD analysis. Our results revealed 140 and 42 SNPs with allelic and genotypic patterns, respectively. Among them, 63 displayed stallion-TRD and 41 exhibited mare-TRD, while 36 SNPs showed overall TRD. In addition, 42 SNPs exhibited heterosis pattern. Functional analyses revealed that the annotated genes located within the TRD regions identified were associated with biological processes and molecular functions related to spermatogenesis, oocyte division, embryonic development, and hormonal activity. A total of 10 functional candidate genes related to fertility were found. To our knowledge, this is the most extensive study performed to evaluate the presence of alleles and functional candidate genes with transmission ratio distortion affecting reproductive performance in the domestic horse.Fil: Laseca, Nora. Universidad de Córdoba; EspañaFil: Cánovas, Ángela. University of Guelph; CanadáFil: Valera, Mercedes. Universidad de Sevilla; EspañaFil: Id Lahoucine, Samir. Scotland’s Rural College; Reino UnidoFil: Perdomo González, Davinia Isabel. Universidad de Sevilla; EspañaFil: Fonseca, Pablo A. S.. Universidad de León; EspañaFil: Demyda-peyrás, Sebastian. Universidad de Córdoba; España. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Molina, Antonio. Universidad de Córdoba; Españ

Unravelling the genetics of non-random fertilization associated with gametic incompatibility

In the dairy industry, mate allocation is dependent on the producer’s breeding goals and the parents’ breeding values. The probability of pregnancy differs among sire-dam combinations, and the compatibility of a pair may vary due to the combination of gametic haplotypes. Under the hypothesis that incomplete incompatibility would reduce the odds of fertilization, and complete incompatibility would lead to a non-fertilizing or lethal combination, deviation from Mendelian inheritance expectations would be observed for incompatible pairs. By adding an interaction to a transmission ratio distortion (TRD) model, which detects departure from the Mendelian expectations, genomic regions linked to gametic incompatibility can be identified. This study aimed to determine the genetic background of gametic incompatibility in Holstein cattle. A total of 283,817 genotyped Holstein trios were used in a TRD analysis, resulting in 422 significant regions, which contained 2075 positional genes further investigated for network, overrepresentation, and guilt-by-association analyses. The identified biological pathways were associated with immunology and cellular communication and a total of 16 functional candidate genes were identified. Further investigation of gametic incompatibility will provide opportunities to improve mate allocation for the dairy cattle industry

Genetic mechanisms underlying spermatic and testicular traits within and among cattle breeds: systematic review and prioritization of GWAS results1

[EN] Reduced bull fertility imposes economic losses in bovine herds. Specifically, testicular and spermatic traits are important indicators of reproductive efficiency. Several genome-wide association studies (GWAS) have identified genomic regions associated with these fertility traits. The aims of this study were as follows: 1) to perform a systematic review of GWAS results for spermatic and testicular traits in cattle and 2) to identify key functional candidate genes for these traits. The identification of functional candidate genes was performed using a systems biology approach, where genes shared between traits and studies were evaluated by a guilt by association gene prioritization (GUILDify and ToppGene software) in order to identify the best functional candidates. These candidate genes were integrated and analyzed breeds. Results showed that GWAS for testicular-related traits have been developed for beef breeds only, whereas the majority of GWAS for spermatic-related traits were conducted using dairy breeds. comparing traits measured within the same study, the highest number of genes shared between different traits was observed, indicating a high impact of the population genetic structure and environmental effects. Several chromosomal regions were enriched for functional candidate genes associated with fertility traits. Moreover, multiple functional candidate genes were enriched for markers in a species-specific basis, taurine (Bos taurus) or indicine (Bos indicus). For the different candidate regions identified in the GWAS in the literature, functional candidate genes were detected as follows: B. Taurus chromosome X (BTX) (TEX11, IRAK, CDK16, ATP7A, ATRX, HDAC6, FMR1, L1CAM, MECP2, etc.), BTA17 (TRPV4 and DYNLL1), and BTA14 (MOS, FABP5, ZFPM2). These genes are responsible for regulating metabolic pathways or biological processes associated with fertility, such as progression of spermatogenesis, control of ciliary activity, development of Sertoli cells, DNA integrity in spermatozoa, and homeostasis of testicular cells. This study represents the first systematic review on male fertility traits in cattle using a system biology approach to identify key candidate genes for these traits.S

Combining multi-OMICs information to identify key-regulator genes for pleiotropic effect on fertility and production traits in beef cattle

[EN] The identification of biological processes related to the regulation of complex traits is a difficult task. Commonly, complex traits are regulated through a multitude of genes contributing each to a small part of the total genetic variance. Additionally, some loci can simultaneously regulate several complex traits, a phenomenon defined as pleiotropy. The lack of understanding on the biological processes responsible for the regulation of these traits results in the decrease of selection efficiency and the selection of undesirable hitchhiking effects. The identification of pleiotropic key-regulator genes can assist in developing important tools for investigating biological processes underlying complex traits. A multi-breed and multi-OMICs approach was applied to study the pleiotropic effects of key-regulator genes using three independent beef cattle populations evaluated for fertility traits. A pleiotropic map for 32 traits related to growth, feed efficiency, carcass and meat quality, and reproduction was used to identify genes shared among the different populations and breeds in pleiotropic regions. Furthermore, data-mining analyses were performed using the Cattle QTL database (CattleQTLdb) to identify the QTL category annotated in the regions around the genes shared among breeds. This approach allowed the identification of a main gene network (composed of 38 genes) shared among breeds. This gene network was significantly associated with thyroid activity, among other biological processes, and displayed a high regulatory potential. In addition, it was possible to identify genes with pleiotropic effects related to crucial biological processes that regulate economically relevant traits associated with fertility, production and health, such as MYC, PPARG, GSK3B, TG and IYD genes. These genes will be further investigated to better understand the biological processes involved in the expression of complex traits and assist in the identification of functional variants associated with undesirable phenotypes, such as decreased fertility, poor feed efficiency and negative energetic balance.SIThis research was supported by the Beef Farmers of Ontario, OMAFRA (Ontario Ministry of Agriculture, Food and Rural Affairs), Beef Cattle Research Council (BCRC), NSERC (Natural Sciences and Engineering Research Council) and Ontario Centres of Excellence (OCE). MRSC is supported by a fellowship from the Brazilian National Research Council (CNPq 312068/2015-8) and grants from the Fundac¸ão de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG, APQ APQ-01377-17 and APQ-01377-17). PASF is supported by a fellowship from the Brazilian National Research Council. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscrip

Precisión y optimización de la evaluación genómica para el peso corporal y la resistencia a enfermedades en el cultivo de salmón

Nowadays, molecular information has changed the way genetic improvement is per-formed, increasing the response to selection from the traditional approach, based only on genealogical information using best linear unbiased prediction (BLUP). In this study, breeding values accuracy obtained using molecular information (using single nucleotide polymorphism (SNP) arrays chip at different densities and whole genome sequence) ware compared by cross validation with BLUP. Three characters of economic interest to the salmon industry were used: body weight at harvest (BW) and resistance to two diseases (caused by pathogens Piscirickettsia salmonis (SRS) and Caligus rogercresseyi (CAL)). The effect of genetic architecture (heritability 'h2'), different trait types (continuous/discrete) and family structure were also taken into account. A typical scheme of fish farming based on families of siblings was simulated: 10 and 50 families with 500 and 100 full-sibs, respectively. Results showed a law of diminishing returns in genomic accuracy when increasing in SNPs chip density. Generally, the use of high number of SNPs or whole genome sequence may not be advantageous compared to medium density SNPs chip (besides the costs involved). The family structure had a clear effect on genomic accuracy for variability in the population. The best genomic evaluation accuracies were observed when few families (10) with few founder individuals (many females for one male) were considered. The relative improvements when using molecular information compared with the accuracy reached by BLUPs method was higher for BW character, continuous of high h2 (0,4), reaching an improvement in accuracy of 24%. For the CAL resistance character, continuous of low h2 (0,1), a maximum 9% of improvement in accuracy is obtained. The SRS resistance character, a binary character with h2 of 0,18, had a loss of accuracy in comparison with continuous character which (on the same level h2), have a 10% of improvement in accuracy. In the case of many families (50), improvements in accuracy were minimal, as BLUP predicted better when there was more variability between individuals. In general, to optimize SNP chip densities, densities of 5k-25k have high enough accuracies. The range of accuracy are 0,70-0,74 for the BW character (continuous at high h2), 0,61-0,67 for the CAL character (continuos of low h2) and 0,62-0,68 for the SRS character (binary whit h2= 0,18) depending on the family structure and SNPs density. Keywords: Molecular information, Genomic selection, BLUP, Disease resistance, Body weight, Salmon farming.Avui dia, la millora genètica s'ha vist revolucionada amb l'ús de la informació molecular, que permet augmentar la resposta a la selecció respecte l'enfocament tradicional, basat només en la informació genealògica usant la millor predicció lineal no esbiaixada (Best Linear Unbiased Prediction, BLUP). En aquest estudi, es va comparar per validació creuada la precisió de la predicció dels valors genètics utilitzant l'avaluació genòmica (usant diferents densitats de polimorfismes d'un sol nucleòtid (SNPs) i seqüència completa) amb el model BLUP. Es van utilitzar tres caràcters d'interès econòmic per a la indústria del salmó: pes corporal a collita (BW) i resistència a dues malalties (causades pels patògens Piscirickettsia salmonis (SRS) i Caligus rogercresseyi (CAL), respectivament). On s'ha avaluat l'efecte de l'arquitectura genètica (heredabilitat 'h2'), el tipus de caràcter (continu / discret) i l'estructura familiar. S'ha seguit l'esquema típic del cultiu aqüícola basat en les famílies de germans on es van simular diferents famílies de diferents mides (10 i 50 famílies de 500 i 100 germans complets, respectivament). Els resultats van mostrar que hi ha un rendiment decreixent de precisió genòmica amb l'augment de la densitat de SNPs. I en general, l'ús d'altes densitats de SNPs o seqüència completa (amb els costos que impliquen) poden no ser avantatjoses respecte densitats mitjanes de SNPs. L'estructura familiar de la població té un efecte clar sobre els precisions genòmiques per la variabilitat molecular existent., On veiem millores precisions de evaluación genómica es quan hi ha poques famílies (10) amb pocs individus fundadors (moltes femelles per un sol mascle). Les millores relatives de la precisió evaluación genómica respecte el BLUP són més elevades en el caràcter contínua BW, continuo d'alta h2 (0,4), amb una millora en la precisió del 24%. En el caràcter de resistència a CAL, continuo de baixa h2 (0,1), només veiem com màxim un 9% de millora en la precisió, en canvi, el caràcter de resistència a SRS, binari amb una h2 del 0,18, hem observat una pèrdua de precisió en comparació amb els caràcters continus (en el mateix nivell d'heretabilitat), on com a màxim, tenim una millora en la precisió del 10%. En els casos de moltes famílies (50), les millores en la precisió són mínimes, ja que el BLUP prediu millor quan tenim més variabilitat entre els individus. En general, per optimitzar les densitats del chip, densitats del 5k-25k SNPs tenen precisions d'evaluación genómica suficientment altes, on les precisions oscil·len 0,70-0,74 de mitjana en el caràcter BW (continu d'alta h2), 0,61-0,67 al caràcter de resistència a CAL (continu de baixa h2) i 0,62-0,68 en el caràcter de resistència a SRS (binari amb h2= 0,18), depenent de la densitat de SNPs y de l'estructura familiar. Paraules claus: Informació molecular, Selecció genòmica, BLUP, Resistència a malalties, Pes corporal, Cultiu del salmó.Hoy en día, la mejora genética se ha visto revolucionada con el uso de la información molecular, que permite aumentar la respuesta a la selección respecto el enfoque tradicional, basado sólo en información genealógica usando la mejor predicción lineal insesgada (Best Linear Unbiased Prediction, BLUP). En este estudio, se comparó por validación cruzada la precisión de la predicción de los valores genéticos utilizando la evaluación genómica (usando diferentes densidades de polimorfismos de un solo nucleótido (SNP) y secuencia completa) con el modelo BLUP. Se utilizaron tres caracteres de interés económico para la industria del salmón: peso corporal a cosecha (BW) y resistencia a dos enfermedades (causadas por los patógenos Piscirickettsia salmonis (CAL) y Caligus rogercresseyi (SRS), respectivamente). Se evaluó el efecto de la arquitectura genética (heredabilidad 'h2'), el tipo de carácter (continuo/discreto) y la estructura familiar. Se ha seguido el esquema típico del cultivo acuícola basado en las familias de hermanos donde se simularon distintas familias de tamaños diferentes (10 y 50 familias de 500 y 100 hermanos completos, respectivamente). Los resultados mostraron que hay un rendimiento decreciente de precisión genómica con el aumento de la densidad de SNPs. Y en general, el uso de altas densidades de SNPs o secuencia completa (con los costes que implican) pueden no resultar ventajoso respecto densidades medias de SNPs. La estructura familiar de la población tiene un efecto claro sobre las precisiones genómicas por la variabilidad molecular existente. Donde vemos mejores precisiones de evaluación genómica es cuando hay pocas familias (10) con pocos individuos fundadores (muchas hembras por un solo macho). Las mejoras relativas de la precisión de la evaluación genómica respecto el BLUP son más elevadas en el carácter BW, continuo de alta h2 (0,4), con una mejora en la precisión del 24%. En el carácter de resistencia a CAL, continuo de baja h2 (0,1), sólo vemos como máximo un 9% de mejora. En cambio, con el carácter de resistencia a SRS, binario con una h2 de 0,18, se ha observado una pérdida de precisión en comparación con los caracteres continuos (en el mismo nivel de h2), donde como máximo, tenemos una mejora en la precisión del 10 %. En los casos de muchas familias (50), las mejoras en la precisión son mínimas, ya que el BLUP predice mejor cuando tenemos más variabilidad entre los individuos. En general, para optimizar las densidades del chip, densidades del 5k-25k SNPs tienen precisiones de evaluación genómica suficientemente altas respecto el BLUP, donde las precisiones oscilan 0,70-0,74 de media en el carácter BW (continuo de alta h2), 0,61-0,67 en el carácter de resistencia a CAL (continuo de baja h2) y 0,62-0,68 en el carácter de resistencia a SRS (binario con h2= 0,18), dependiendo de la densidad de SNPs y de la estructura familiar. Palabras claves: Información molecular, Selección genómica, BLUP, Resistencia a enfermedades, Peso corporal, Cultivo del salmón

Precisión y optimización de la evaluación genómica para el peso corporal y la resistencia a enfermedades en el cultivo de salmón

Nowadays, molecular information has changed the way genetic improvement is per-formed, increasing the response to selection from the traditional approach, based only on genealogical information using best linear unbiased prediction (BLUP). In this study, breeding values accuracy obtained using molecular information (using single nucleotide polymorphism (SNP) arrays chip at different densities and whole genome sequence) ware compared by cross validation with BLUP. Three characters of economic interest to the salmon industry were used: body weight at harvest (BW) and resistance to two diseases (caused by pathogens Piscirickettsia salmonis (SRS) and Caligus rogercresseyi (CAL)). The effect of genetic architecture (heritability 'h2'), different trait types (continuous/discrete) and family structure were also taken into account. A typical scheme of fish farming based on families of siblings was simulated: 10 and 50 families with 500 and 100 full-sibs, respectively. Results showed a law of diminishing returns in genomic accuracy when increasing in SNPs chip density. Generally, the use of high number of SNPs or whole genome sequence may not be advantageous compared to medium density SNPs chip (besides the costs involved). The family structure had a clear effect on genomic accuracy for variability in the population. The best genomic evaluation accuracies were observed when few families (10) with few founder individuals (many females for one male) were considered. The relative improvements when using molecular information compared with the accuracy reached by BLUPs method was higher for BW character, continuous of high h2 (0,4), reaching an improvement in accuracy of 24%. For the CAL resistance character, continuous of low h2 (0,1), a maximum 9% of improvement in accuracy is obtained. The SRS resistance character, a binary character with h2 of 0,18, had a loss of accuracy in comparison with continuous character which (on the same level h2), have a 10% of improvement in accuracy. In the case of many families (50), improvements in accuracy were minimal, as BLUP predicted better when there was more variability between individuals. In general, to optimize SNP chip densities, densities of 5k-25k have high enough accuracies. The range of accuracy are 0,70-0,74 for the BW character (continuous at high h2), 0,61-0,67 for the CAL character (continuos of low h2) and 0,62-0,68 for the SRS character (binary whit h2= 0,18) depending on the family structure and SNPs density. Keywords: Molecular information, Genomic selection, BLUP, Disease resistance, Body weight, Salmon farming.Avui dia, la millora genètica s'ha vist revolucionada amb l'ús de la informació molecular, que permet augmentar la resposta a la selecció respecte l'enfocament tradicional, basat només en la informació genealògica usant la millor predicció lineal no esbiaixada (Best Linear Unbiased Prediction, BLUP). En aquest estudi, es va comparar per validació creuada la precisió de la predicció dels valors genètics utilitzant l'avaluació genòmica (usant diferents densitats de polimorfismes d'un sol nucleòtid (SNPs) i seqüència completa) amb el model BLUP. Es van utilitzar tres caràcters d'interès econòmic per a la indústria del salmó: pes corporal a collita (BW) i resistència a dues malalties (causades pels patògens Piscirickettsia salmonis (SRS) i Caligus rogercresseyi (CAL), respectivament). On s'ha avaluat l'efecte de l'arquitectura genètica (heredabilitat 'h2'), el tipus de caràcter (continu / discret) i l'estructura familiar. S'ha seguit l'esquema típic del cultiu aqüícola basat en les famílies de germans on es van simular diferents famílies de diferents mides (10 i 50 famílies de 500 i 100 germans complets, respectivament). Els resultats van mostrar que hi ha un rendiment decreixent de precisió genòmica amb l'augment de la densitat de SNPs. I en general, l'ús d'altes densitats de SNPs o seqüència completa (amb els costos que impliquen) poden no ser avantatjoses respecte densitats mitjanes de SNPs. L'estructura familiar de la població té un efecte clar sobre els precisions genòmiques per la variabilitat molecular existent., On veiem millores precisions de evaluación genómica es quan hi ha poques famílies (10) amb pocs individus fundadors (moltes femelles per un sol mascle). Les millores relatives de la precisió evaluación genómica respecte el BLUP són més elevades en el caràcter contínua BW, continuo d'alta h2 (0,4), amb una millora en la precisió del 24%. En el caràcter de resistència a CAL, continuo de baixa h2 (0,1), només veiem com màxim un 9% de millora en la precisió, en canvi, el caràcter de resistència a SRS, binari amb una h2 del 0,18, hem observat una pèrdua de precisió en comparació amb els caràcters continus (en el mateix nivell d'heretabilitat), on com a màxim, tenim una millora en la precisió del 10%. En els casos de moltes famílies (50), les millores en la precisió són mínimes, ja que el BLUP prediu millor quan tenim més variabilitat entre els individus. En general, per optimitzar les densitats del chip, densitats del 5k-25k SNPs tenen precisions d'evaluación genómica suficientment altes, on les precisions oscil·len 0,70-0,74 de mitjana en el caràcter BW (continu d'alta h2), 0,61-0,67 al caràcter de resistència a CAL (continu de baixa h2) i 0,62-0,68 en el caràcter de resistència a SRS (binari amb h2= 0,18), depenent de la densitat de SNPs y de l'estructura familiar. Paraules claus: Informació molecular, Selecció genòmica, BLUP, Resistència a malalties, Pes corporal, Cultiu del salmó.Hoy en día, la mejora genética se ha visto revolucionada con el uso de la información molecular, que permite aumentar la respuesta a la selección respecto el enfoque tradicional, basado sólo en información genealógica usando la mejor predicción lineal insesgada (Best Linear Unbiased Prediction, BLUP). En este estudio, se comparó por validación cruzada la precisión de la predicción de los valores genéticos utilizando la evaluación genómica (usando diferentes densidades de polimorfismos de un solo nucleótido (SNP) y secuencia completa) con el modelo BLUP. Se utilizaron tres caracteres de interés económico para la industria del salmón: peso corporal a cosecha (BW) y resistencia a dos enfermedades (causadas por los patógenos Piscirickettsia salmonis (CAL) y Caligus rogercresseyi (SRS), respectivamente). Se evaluó el efecto de la arquitectura genética (heredabilidad 'h2'), el tipo de carácter (continuo/discreto) y la estructura familiar. Se ha seguido el esquema típico del cultivo acuícola basado en las familias de hermanos donde se simularon distintas familias de tamaños diferentes (10 y 50 familias de 500 y 100 hermanos completos, respectivamente). Los resultados mostraron que hay un rendimiento decreciente de precisión genómica con el aumento de la densidad de SNPs. Y en general, el uso de altas densidades de SNPs o secuencia completa (con los costes que implican) pueden no resultar ventajoso respecto densidades medias de SNPs. La estructura familiar de la población tiene un efecto claro sobre las precisiones genómicas por la variabilidad molecular existente. Donde vemos mejores precisiones de evaluación genómica es cuando hay pocas familias (10) con pocos individuos fundadores (muchas hembras por un solo macho). Las mejoras relativas de la precisión de la evaluación genómica respecto el BLUP son más elevadas en el carácter BW, continuo de alta h2 (0,4), con una mejora en la precisión del 24%. En el carácter de resistencia a CAL, continuo de baja h2 (0,1), sólo vemos como máximo un 9% de mejora. En cambio, con el carácter de resistencia a SRS, binario con una h2 de 0,18, se ha observado una pérdida de precisión en comparación con los caracteres continuos (en el mismo nivel de h2), donde como máximo, tenemos una mejora en la precisión del 10 %. En los casos de muchas familias (50), las mejoras en la precisión son mínimas, ya que el BLUP predice mejor cuando tenemos más variabilidad entre los individuos. En general, para optimizar las densidades del chip, densidades del 5k-25k SNPs tienen precisiones de evaluación genómica suficientemente altas respecto el BLUP, donde las precisiones oscilan 0,70-0,74 de media en el carácter BW (continuo de alta h2), 0,61-0,67 en el carácter de resistencia a CAL (continuo de baja h2) y 0,62-0,68 en el carácter de resistencia a SRS (binario con h2= 0,18), dependiendo de la densidad de SNPs y de la estructura familiar. Palabras claves: Información molecular, Selección genómica, BLUP, Resistencia a enfermedades, Peso corporal, Cultivo del salmón