¿Can crossbred animals be used for genomic selection?

Ponencia publicada en ITEA, vol.104La producción en poblaciones “puras” suele tener una baja reproducibilidad en sus descendentes “cruzados”. La selección genómica podría utilizarse para evaluar poblaciones “puras” usando los datos de sus descendientes “cruzados”. Sin embargo, en las poblaciones cruzadas quizás el desequilibrio de ligamiento (LD) no esta restringido a marcadores estrechamente ligados al QTL y los efectos de los marcadores podrían ser específicos de cada población. Estos dos problemas podrían solucionarse utilizando un modelo con los alelos de los SNPs específicos para cada población. Para investigar esta idea usamos un modelo con los efectos de los genotipos de los SNPs (modelo 1) y otro modelo con los efectos de alelos de los SNPs específicos para cada población (modelo 2). Ambos modelos se utilizaron para predecir los valores genéticos de las poblaciones “puras” usando datos F1. Tres situaciones fueron simuladas, en las dos primeras se consideró que las dos poblaciones tenían un mismo origen con una diferencia de 50 y 550 generaciones, respectivamente. En la tercera situación se consideró que las dos poblaciones tenían orígenes distintos. En todos los casos las dos poblaciones generaron una población F1 con un tamaño de 1.000 individuos. Los valores fenotípicos de la F1 fueron simulados con una media de 12 QTL segregando y una heredabilidad de 0.3. En el análisis de la F1 y la población “pura” de validación se escogieron 500 marcadores en segregación. Para estimar el efecto de los SNPs se utilizó el método Bayesiano llamado Bayes-B. La precisión media de los valores genéticos obtenida varió entre 0.789 y 0.718. Sin embargo, se observó que conforme las poblaciones estuvieron más alejadas la precisión disminuyó y el modelo 2 dio valores ligeramente superiores que el modelo 1. Estos resultados sugerirían que los animales cruzados pueden ser utilizados para evaluar poblaciones “puras”. Además modelos con origen específico de población darían mejores resultados.Performance of purebred parents can be a poor predictor of performance of their crossbred descendants. However, in crossbred populations linkage disequilibrium may not be restricted to markers that are tightly linked to the QTL and the effects of SNPs may be breed specific. Both these problems can be addressed by using a model with breed-specific SNP effects. To investigate this idea, we used a model with effects of SNP genotypes (model 1) and a model with breed-specific effects of SNP alleles (model 2) to predict purebred breeding values using F1 data. Three scenarios were considered. In the first two, pure breeds were assumed to have a common origin either 50 or 550 generations ago. In the third scenario, the two breeds did not have a common origin. In all these scenarios, the two breeds were used to generate an F1 with 1,000 individuals. Trait phenotypic values controlled by 12 segregating QTL and with a heritability of 0.30 were simulated for the F1 individuals. Further, 500 segregating markers on a chromosome of 1 Morgan were chosen for analysis in the F1s and in the validation population of purebred. A Bayesian method (Bayes-B) was used to estimate the SNP effects. The accuracy of the predictions was between 0.789 and 0.718. However, the accuracy was lower when the populations were more separate and model 2 gave values slightly higher than model 1. These results suggest that crossbred data could be used to evaluate purebreds and breed specific models could give better results

Optimum selection for quantitative traits with information on an identified locus in outbred populations.

Methods to formulate and maximize response to selection for a quantitative trait over multiple generations when information on a quantitative trait locus (major gene) is available were developed to investigate and optimize response to selection in mixed inheritance models. Deterministic models with and without gametic phase disequilibrium between the major gene and other genes that affect the trait (polygenes) were considered. Genetic variance due to polygenes was assumed constant. Optimal control theory was used to formulate selection on an index of major gene effects and estimates of polygenic breeding values and to derive index weights that maximize cumulative response over multiple generations. Optimum selection strategies were illustrated using an example and compared with mass selection and with selection with full emphasis on the major gene (genotypic selection). The latter maximizes the single-generation response for a major gene with additive effects. For the example considered, differences between selection methods in cumulative response at the end of a planning horizon of 5, 10, or 15 generations were small but responses were greatest for optimum selection. Genotypic selection had the greatest response in the short term but the lowest response in the longer term. For optimum selection, emphasis on the major gene changed over generations. However, when accounting for variance contributed by the major gene, optimum selection resulted in approximately constant selection pressure on the major gene and polygenes over generations. Suboptimality of genotypic selection in the longer term was caused not so much by gametic phase disequilibrium but rather by unequal selection pressure on the major gene (and, therefore, on polygenes) over generations, as frequency and variance at the major gene changed. Extension of methods to more complex breeding structures, genetic models and objective functions is discussed